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Weka Tutorial 02: Data Preprocessing 101 (Data Preprocessing)
 
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This tutorial demonstrates various preprocessing options in Weka. However, details about data preprocessing will be covered in the upcoming tutorials.
Views: 154824 Rushdi Shams
How to Sort CSV files and lists in Python
 
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This is a tutorial concerning how to sort CSV files and lists easily within python by column. The logic possibly by programming plus the simplicity of being able to sort columns makes python a superb choice for managing CSV documents and lists that are delimited by something. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 41621 sentdex
How to Import Data, Copy Data from Excel to R: .csv & .txt Formats (R Tutorial 1.5)
 
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Import/copy data from excel (or other spreadsheets) into #R using both comma-separated values and tab-delimited text file. Find more #RStats and #Statistics Tutorials here: https://goo.gl/4vDQzT ▶︎ You will learn to use "read.csv", "read.delim" and "read.table" commands along with "file.choose", "header", and "sep" arguments. This video is a tutorial for programming in #RStatisticalSoftware and #RStudio for beginners. You can access the dataset here: our website: http://www.statslectures.com/index.php/r-stats-videos-tutorials/getting-started-with-r/1-3-import-excel-data or here: Excel Data Used in This Video: http://bit.ly/1uyxR3O Excel Data Used in Subsequent Videos: https://bit.ly/LungCapDataxls Tab Delimited Text File Used in Subsequent Videos: https://bit.ly/LungCapData ◼︎Here is a quick overview of the topics addressed in this video; click on time stamps to jump to a specific topic: 0:00:17 the two main file types for saving a data file 0:00:36 how to save a file in excel as a csv file ("comma-separated value") 0:01:10 how to open a comma-separated (.csv) data file into excel 0:01:20 how to open a comma-separated (.csv) data file into a text editor 0:01:36 how to import comma-separated (.csv) data file into R using "read.csv" command 0:01:44 how to access the help menu for different commands in R 0:02:04 how to use "file.choose" argument on "read.csv" command to specify the file location in R 0:02:31 how to use the "header" argument on "read.csv" command to let R know that data has headers or variable names 0:03:22 how to import comma-separated (.csv) data file into R using "read.table" command 0:03:38 how to use "file.choose" argument on "read.table" command to specify the file location in R 0:03:41 how to use the "header" argument on "read.table" command to let R know the data has headers or variable names 0:03:46 how to use the "sep" argument on "read.table" command to let R know how the data values are separated 0:04:10 how to save a file in excel as tab-delimited text file 0:04:50 how to open a tab-delimited (.txt) data file into a text editor 0:05:07 how to open a tab-delimited (.txt) data file into excel 0:05:20 how to import tab-delimited (.txt) data file into R using "read.delim" command 0:05:44 how to use "file.choose" argument on "read.delim" command to specify the file path in R 0:05:49 how to use the "header" argument on "read.delim" command to let R know that the data has headers or variable 0:06:06 how to import tab-delimited (.txt) data file into R using "read.table" command 0:06:20 how to use "file.choose" argument on "read.table" command to specify the file location 0:06:23 how to use the "header" argument on "read.table" command to let R know that the data has headers or variable names 0:06:27 how to use the "sep" argument on "read.table" command to let R know how the data values are separated *****************************************************************************************To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at #UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH)
Importing Data and Working With Data in R (R Tutorial 1.6)
 
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Learn how to import a dataset into R and begin to work with data. You will learn the "read.table", "header", "sep", "file.choose", "dim", "head", "tail", "as.factor", "attach", "detach", "levels", and [] commands. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset from our website: http://www.statslectures.com/index.php/r-stats-datasets or here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics addressed in this video; You can click on the time stamp to jump to the specific topic. 0:00:07 how to read a dataset into R using "read.table" command and save it as an object 0:00:27 how to access the help menu in R 0:01:02 how to let R know that the first row of our data is headers by using "header" argument 0:01:14 how to let R know how the observations are separated by using "sep" argument 0:02:03 how to specify the path to the file using "file.choose" argument on the "read.table" command 0:03:15 how to use Menu options to import data into R when working with RStudio 0:05:23 how to use Excel to prepare the data for using in R 0:06:15 how to know the dimensions (the number of rows and columns) of the data in R using the "dim" command 0:06:35 how to see the first six rows of the data in R using the "head" command 0:06:45 how to see the last six rows of the data in R using the "tail" command 0:07:18 how to check if the data was read correctly into R using square brackets and subsetting data 0:08:21 how to check the variable names in R using the "names" command http://statslectures.com/index.php
Let's Automate Instagram without using the API - Web Automation Screen Scraping with PHP and cURL
 
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In this video I tactically automate Instagram to extract Recent Posts. Instead of using the API I use screen scraping to get started fast and treat the Application as an API. ► An introduction to PHP ► An overview of REGEX in PHP ► Screen Scraping Web Site using PHP ► Processing JSON in PHP ► Add assertions to live code to guard against application changes - previously talked about APP as API - here is a good example - Instagram have an API which requires a dev key etc. - But instagram also have a GUI which does not require logging in or API key - Instagram GUI is primarily JavaScript based i.e. when we issue a request we don't get an HTML page we get a page dyanmically created from an embedded JSON payload - To automate then: - call the page - treat most of the page as a header - treat most of the page as a footer - pull out the embedded JSON and parse - There are risks to this: - it isn't an official API - they might change the JSON - they might change the page format - there are many ways this might break - so code against those ways and assert on your expectations - walk through the PHP code that does this See also my video on Ruthless Efficiency where I start to automate Instagram - https://www.youtube.com/watch?v=MBQWxRRr_-U ************* ► Subscribe to My Channel For more videos like this http://www.youtube.com/subscription_center?add_user=EvilTesterVideos ************* ►► Contact Details: Read my writing and blogs at: ✓ http://www.eviltester.com ✓ http://www.seleniumsimplified.com ✓ http://www.javafortesters.com ✓ http://www.compendiumdev.co.uk Follow me on social media: ★ https://uk.linkedin.com/in/eviltester ★ https://twitter.com/eviltester - @eviltester ★ https://www.instagram.com/eviltester/ ★ https://uk.pinterest.com/eviltester/ ************* ►► Read my books http://compendiumdev.co.uk/page/books ★ "Dear Evil Tester" - explore the tester's mind ★ "Java For Testers" - learn to code in Java ★ "Automating and Testing a REST API - a case study" ************* ►►Learn skills from my online training courses http://www.compendiumdev.co.uk/page/online_training ★ Selenium WebDriver With Java ★ Technical Web Testing 101 ★ Evil Tester Talks Technical Testing ★ Case Study: Java Desktop Application Technical Training *************
1.4: Twitter API - Understanding & simplifying JSON response.
 
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Lets Code! In this video we will understand and simplify the response returned in JSON format. We will parse the response using json_decode() function and convert it to an Array. We will then retrieve the names of elements we want the script to display. You can refer the Twitter Documentation Site for example response texts and extract the exact names of elements. This video provides steps on how to display the information from JSON response by first converting it to an Array and then iterating through the elements. Twitter API Documentation : https://dev.twitter.com/docs Example Response: https://dev.twitter.com/rest/reference/get/statuses/user_timeline Connect: https://twitter.com/venkymudaliar
Views: 743 Venkatesh Mudaliar
how to spoof referer http with fiddlre
 
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in this tutorial i make u how to capture traffic and then modify it as an example i use level3 of spoofing from enigmagroup a site were u can lear to hack. what im going to change is the http header referer to enter a new value
Views: 3728 XXZeroZero1
Which2Gui - defect prediction data mining software for the masses
 
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Which2 is an instance based learner written in lisp, designed to discover rules that predict for given classes. Which2Gui is a graphic interface written in python that sits on top of Which2 and provides a pretty box to look at while datamining.
Views: 162 aperhins
Twitter Analytics with Power BI
 
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Import Twitter Data (Twitter Search) in Power BI! If you are a member of Curbal.com (it is free), you can download the file here: http://curbal.com/blog/discover-and-analyze-what-people-are-saying-in-twitter-about-your-company-with-power-bi Keynotes: Chris Koester Blog: 00:24 Create a Twitter API key 00:52 Import Twitter data into Power BI 03:18 Create a Parameters for Twitter Search 05:53 Create the first Twitter Report 08:01 Clean Twitter data with Power Query 08:20 Link to Chris' blog post: http://chris.koester.io/index.php/2015/07/16/get-data-from-twitter-api-with-power-query/ Looking for a download file? Go to our Download Center: https://curbal.com/donwload-center SUBSCRIBE to learn more about Power and Excel BI! https://www.youtube.com/channel/UCJ7UhloHSA4wAqPzyi6TOkw?sub_confirmation=1 Our PLAYLISTS: - Join our DAX Fridays! Series: https://goo.gl/FtUWUX - Power BI dashboards for beginners: https://goo.gl/9YzyDP - Power BI Tips & Tricks: https://goo.gl/H6kUbP - Power Bi and Google Analytics: https://goo.gl/ZNsY8l ABOUT CURBAL: Website: http://www.curbal.com Contact us: http://www.curbal.com/contact ▼▼▼▼▼▼▼▼▼▼ If you feel that any of the videos, downloads, blog posts that I have created have been useful to you and you want to help me keep on going, here you can do a small donation to support my work and keep the channel running: https://curbal.com/product/sponsor-me Many thanks in advance! ▲▲▲▲▲▲▲▲▲▲ QUESTIONS? COMMENTS? SUGGESTIONS? You’ll find me here: ► Twitter: @curbalen, @ruthpozuelo ► Google +: https://goo.gl/rvIBDP ► Facebook: https://goo.gl/bME2sB ► Linkedin: https://goo.gl/3VW6Ky
Views: 7771 Curbal
How to Clean Up Raw Data in Excel
 
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Al Chen (https://twitter.com/bigal123) is an Excel aficionado. Watch as he shows you how to clean up raw data for processing in Excel. This is also a great resource for data visualization projects. Subscribe to Skillshare’s Youtube Channel: http://skl.sh/yt-subscribe Check out all of Skillshare’s classes: http://skl.sh/youtube Like Skillshare on Facebook: https://www.facebook.com/skillshare Follow Skillshare on Twitter: https://twitter.com/skillshare Follow Skillshare on Instagram: http://instagram.com/Skillshare
Views: 62069 Skillshare
Weka Text Classification for First Time & Beginner Users
 
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59-minute beginner-friendly tutorial on text classification in WEKA; all text changes to numbers and categories after 1-2, so 3-5 relate to many other data analysis (not specifically text classification) using WEKA. 5 main sections: 0:00 Introduction (5 minutes) 5:06 TextToDirectoryLoader (3 minutes) 8:12 StringToWordVector (19 minutes) 27:37 AttributeSelect (10 minutes) 37:37 Cost Sensitivity and Class Imbalance (8 minutes) 45:45 Classifiers (14 minutes) 59:07 Conclusion (20 seconds) Some notable sub-sections: - Section 1 - 5:49 TextDirectoryLoader Command (1 minute) - Section 2 - 6:44 ARFF File Syntax (1 minute 30 seconds) 8:10 Vectorizing Documents (2 minutes) 10:15 WordsToKeep setting/Word Presence (1 minute 10 seconds) 11:26 OutputWordCount setting/Word Frequency (25 seconds) 11:51 DoNotOperateOnAPerClassBasis setting (40 seconds) 12:34 IDFTransform and TFTransform settings/TF-IDF score (1 minute 30 seconds) 14:09 NormalizeDocLength setting (1 minute 17 seconds) 15:46 Stemmer setting/Lemmatization (1 minute 10 seconds) 16:56 Stopwords setting/Custom Stopwords File (1 minute 54 seconds) 18:50 Tokenizer setting/NGram Tokenizer/Bigrams/Trigrams/Alphabetical Tokenizer (2 minutes 35 seconds) 21:25 MinTermFreq setting (20 seconds) 21:45 PeriodicPruning setting (40 seconds) 22:25 AttributeNamePrefix setting (16 seconds) 22:42 LowerCaseTokens setting (1 minute 2 seconds) 23:45 AttributeIndices setting (2 minutes 4 seconds) - Section 3 - 28:07 AttributeSelect for reducing dataset to improve classifier performance/InfoGainEval evaluator/Ranker search (7 minutes) - Section 4 - 38:32 CostSensitiveClassifer/Adding cost effectiveness to base classifier (2 minutes 20 seconds) 42:17 Resample filter/Example of undersampling majority class (1 minute 10 seconds) 43:27 SMOTE filter/Example of oversampling the minority class (1 minute) - Section 5 - 45:34 Training vs. Testing Datasets (1 minute 32 seconds) 47:07 Naive Bayes Classifier (1 minute 57 seconds) 49:04 Multinomial Naive Bayes Classifier (10 seconds) 49:33 K Nearest Neighbor Classifier (1 minute 34 seconds) 51:17 J48 (Decision Tree) Classifier (2 minutes 32 seconds) 53:50 Random Forest Classifier (1 minute 39 seconds) 55:55 SMO (Support Vector Machine) Classifier (1 minute 38 seconds) 57:35 Supervised vs Semi-Supervised vs Unsupervised Learning/Clustering (1 minute 20 seconds) Classifiers introduces you to six (but not all) of WEKA's popular classifiers for text mining; 1) Naive Bayes, 2) Multinomial Naive Bayes, 3) K Nearest Neighbor, 4) J48, 5) Random Forest and 6) SMO. Each StringToWordVector setting is shown, e.g. tokenizer, outputWordCounts, normalizeDocLength, TF-IDF, stopwords, stemmer, etc. These are ways of representing documents as document vectors. Automatically converting 2,000 text files (plain text documents) into an ARFF file with TextDirectoryLoader is shown. Additionally shown is AttributeSelect which is a way of improving classifier performance by reducing the dataset. Cost-Sensitive Classifier is shown which is a way of assigning weights to different types of guesses. Resample and SMOTE are shown as ways of undersampling the majority class and oversampling the majority class. Introductory tips are shared throughout, e.g. distinguishing supervised learning (which is most of data mining) from semi-supervised and unsupervised learning, making identically-formatted training and testing datasets, how to easily subset outliers with the Visualize tab and more... ---------- Update March 24, 2014: Some people asked where to download the movie review data. It is named Polarity_Dataset_v2.0 and shared on Bo Pang's Cornell Ph.D. student page http://www.cs.cornell.edu/People/pabo/movie-review-data/ (Bo Pang is now a Senior Research Scientist at Google)
Views: 130113 Brandon Weinberg
Let’s Write a Decision Tree Classifier from Scratch - Machine Learning Recipes #8
 
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Hey everyone! Glad to be back! Decision Tree classifiers are intuitive, interpretable, and one of my favorite supervised learning algorithms. In this episode, I’ll walk you through writing a Decision Tree classifier from scratch, in pure Python. I’ll introduce concepts including Decision Tree Learning, Gini Impurity, and Information Gain. Then, we’ll code it all up. Understanding how to accomplish this was helpful to me when I studied Machine Learning for the first time, and I hope it will prove useful to you as well. You can find the code from this video here: https://goo.gl/UdZoNr https://goo.gl/ZpWYzt Books! Hands-On Machine Learning with Scikit-Learn and TensorFlow https://goo.gl/kM0anQ Follow Josh on Twitter: https://twitter.com/random_forests Check out more Machine Learning Recipes here: https://goo.gl/KewA03 Subscribe to the Google Developers channel: http://goo.gl/mQyv5L
Views: 146958 Google Developers
Carry Document Header  Page to Section Headers on ChronoScan
 
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On this video we will learn how to capture one barcode value from the first document and carry it over to subsequent documents using barcode triggers. http://chronoscan.org/ https://twitter.com/chronoscan https://www.linkedin.com/company/chronoscan-capture https://www.facebook.com/Chronoscan [email protected] [email protected]
XSS Header Injection in Oracle HTTP Server
 
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This is a Proof of concept for the XSS Header Injection in Oracle HTTP Server. In fact, this later does not sanitize the Expect header from an HTTP request when it is reflected back in an error message, which might allow cross-site scripting (XSS) style attacks using web client components that can send arbitrary headers in requests, as demonstrated using a Flash SWF file. More details: http://www.exploit-db.com/exploits/17393/
Views: 11504 Yetanothernickname
Combine Data Sources in Google Data Studio | Lesson 2
 
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In this lesson we're going to setup our data sources in Google Sheets with the help of Supermetrics. We're going to pull data from Facebook Ads and Google Analytics and prepare it to later be used in Google Data Studio. Google Sheets combined with Supermetrics is a great way to control data that later goes into our data dashboards - it gives you the possibility to change data around, clean it up and even combine data sources (which is not possible in Google Data Studio itself). Previous video: http://bit.ly/2f4FgZl #GoogleDataStudio #DataSources #DataVizualisation 🔗 Links mentioned in the video: Google Data Sheet: http://bit.ly/2tUX3EF Full Playlist: http://bit.ly/2hkwUx4 Coding is for Losers: http://codingisforlosers.com/ Ben Collins: http://benlcollins.com/ The Dashboard Plan: https://measureschool.com/dashboardplan Google Data Studio:http://bit.ly/2bcb7zt Google Sheets: http://bit.ly/1GAUvK5 Supermetrics: http://bit.ly/2hmxvOR 🎓 Learn more from Measureschool: http://measureschool.com/products 🚀Looking to kick-start your data journey? Hire us: https://measureschool.com/services/ 📚 Recommended Measure Books: https://kit.com/Measureschool/recommended-measure-books 📷 Gear we used to produce this video: https://kit.com/Measureschool/measureschool-youtube-gear 👍 FOLLOW US FACEBOOK: http://www.facebook.com/measureschool TWITTER: http://www.twitter.com/measureschool
Views: 25501 Measureschool
Bringing BACK The iPhone Headphone Jack - in China
 
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I love my iPhone, but it doesn't have a headphone jack! So I decided to add my own. For real. How I made an iPhone in China video: https://youtu.be/leFuF-zoVzA Share this video: https://youtu.be/utfbE3_uAMA Subscribe to the channel here: https://goo.gl/qeurxc 4 months, 7 custom circuit boards designs, 3 disassembled iPhones later, it works. It's the first modern iPhone with a headphone jack - the only one like it in the world. More details here (and answers to all your questions): http://strangeparts.com/bringing-back-the-iphone-headphone-jack-in-china/ For diehard Strange Parts fans, go here to find out more about how to get a limited edition headphone jack circuit board: http://strangeparts.com/headphones The design is completely open source! Go here to find out more: http://github.com/strangeparts/niubi-headphones I NEED YOUR HELP! Tell me what you'd like to see me do next in the comments! I'm really looking forward to exploring the back alleys of the industrial world outside of just cell phones and China. And if you think you have a really awesome idea, please email [email protected] In particular, if you live somewhere cool (particularly India or Africa), I want to hear about the industrial world(markets/factories/mines/etc) where you live. And if you're an engineer in manufacturing, hit me up with that cool factory story you've been dying to have someone tell. Thanks guys! My Gear: I shot it on this camera: http://amzn.to/2B0Snke And also with this: http://amzn.to/2D7q5pN And recorded sound on this: http://amzn.to/2CFuyPv Collaborative editing software: http://bit.ly/frameio-sp Facebook: http://facebook.com/strangepartscom Twitter: http://twitter.com/strangepartscom Instagram: http://instagram.com/strangeparts_com Email Newsletter: http://strangeparts.com/ Thank you to everyone that helped! Please go check them out - they’re all doing cool stuff. -- Galen - Assistant editor and all around right hand man Junshu - cameraman and filmmaker extraordinaire Colin Shipp - Advisor/Youtube Consultant ([email protected]) Lewis - Translations wizard Nick Starno (http://nickstarno.info) - CNC master Loic De Buck - The keeper of the logic analyzer Ian Lesnet (http://dirtypcbs.com) - Supplier of antique drill presses, scavenged monitors, sage advice, and other curiosities Greg Needel and David Yanoshak - REV Robotics (http://www.revrobotics.com/) - bringers of the wisdom Hans (hmichl) - Electronics insight Paul Campbell (http://www.moonbaseotago.com) - Electronics insight and lore Julong Tool Brothers - The best tool booth in tool alley! Endy - chip brokerh (WeChat: YCJ13691959788) Lisa - Flexible PCB supplier ([email protected]) Music -- Handpan player - Chor Lai (http://facebook.com/chorsharp) Nice To You - Vibe Tracks - Youtube Audio Library Other Scenario - Lana Inspired (licensed through http://bit.ly/artlist-sp) Follow Me - Jimmy Fontanez - Youtube Audio Library Verve - A-GROUP (licensed through http://bit.ly/artlist-sp) Innocence - Suraj Nepal (licensed through http://bit.ly/artlist-sp) Pie Flavor - 0r4 (CC-BY https://soundcloud.com/0r4/pie-flavor) Breath Celebration - Gabriel Meyer (licensed through http://bit.ly/artlist-sp) Glitch garage rmx - faze rock (CC-BY https://soundcloud.com/fazerock/p-glitch-garage-rmx) Paradise - Ryan Little (https://soundcloud.com/iamryanlittle) Year Of Life - Young Rich Pixies (licensed through http://bit.ly/artlist-sp) Long Way - Lush Island (licensed through http://bit.ly/artlist-sp) Endless Inspiration - Nick Petrov (licensed through hooksounds.com) #StrangeParts #iPhoneAdventures #China
Views: 7046172 Strange Parts
Twitter Marketing Bot
 
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All of the tools you need to grow your Twitter audience and engagement! Learn More... https://goo.gl/mo6mZB - Growth * Fans These are your followers that you are not following back. * New Followers The people that have followed you most recently. * Copy Followers Copy followers from an account that has similar content to yours. * Copy Friends Follow the same people someone else is following. * Keywords Search accounts based on a key word or phrase. * Suggestions The accounts Twitter thinks you'll be interested in. * Unfollowers These are people that used to follow you but now do not. * Non Followers The people you follow that have not followed you back. * Inactive Friends The people you are following that haven't tweeted recently. - Engage * Uploader Quickly upload images to your schedule. * Scheduler Set your schedule with recommended times based on your audience's engagement. * RSS Importer Import tweets from an rss feed, quickly. * Search Find relevant content posted on Twitter by other people. * Tweet Schedule a tweet with text and up to 4 images. - Collections * Create Create a new collection of tweets. * Collect Collect tweets from Twitter links, your recent tweets, or your top tweets. * Share Generate a widget for your web page or schedule a tweet with a link to the collection. Get This Awesome Software Click on The Link - https://goo.gl/mo6mZB Twitter Marketing Software Twitter Marketing Product Twitter Marketing Strategy for Business Twitter Marketing Bot Twitter Marketing Tips Twitter Marketing Tools Twitter Marketing 2016 Twitter Effective Marketing Tool Music By - Summer Reggae Hip - Hop Instrumental Beat -- 'Feeling Lucky Today'- EXMGE Music
Extracting Facebook Posts - H2L video
 
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In Informatica Developer, you can read social media data from web sites such as Facebook and LinkedIn. In this demo, we'll see how to use the Developer tool to extract wall posts from the Facebook web site.
Views: 8937 Informatica Support
Connecting To Twitter and Using the Extracted Data in the Mapping - Informatica  Powercenter Express
 
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This video will Guide you to create a Twitter application, Configure Open Authentication using OAuth Utility, Create a twitter connection, Twitter data Object, Twitter Data Object Operation and use it in the mapping in Informatica Developer. For more goto http://a2zinformatica.blogspot.com/2015/01/informatica-powercenter-express_10.html
Views: 1625 Informatica HowTo
Intro to Azure ML: Modules & Experiments
 
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Today we'll explore the interface of our new machine learning tool, Azure ML. How do you bring data to and from the outside world into Azure ML? The import dataset module can read in data from a variety of sources: HTTP, Azure SQL database, Hadoop Hive query, or Azure Storage Blobs. You can also convert the data to a variety of formats, then save them to your local computer. If the data is fairly large, you have access to export the data to other parts of the Azure ecosystem using the export data module. In Part 3 we will cover: - Creating an experiment - Exploring your experiment workspace - Modules - Importing and exporting data -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3500+ employees from over 700 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8mYD0 See what our past attendees are saying here: https://hubs.ly/H0f8n4J0 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... Vimeo: https://vimeo.com/datasciencedojo
Views: 7067 Data Science Dojo
SAP HANA Academy - Text Analysis: 6. MIME Type
 
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In this series of videos, Tahir Hussain Babar examine the Text Analysis functionality available within SAP HANA. In this video, he examines using the MIME Type parameter. Scripts ; https://github.com/saphanaacademy/TextAnalysis_Search_Mining/blob/master/TextAnalysisExamples.txt Thank you for watching. Video by the SAP HANA Academy. SOCIAL MEDIA Feel free to connect with us at the links below: LinkedIn: https://linkedin.com/saphanaacademy Twitter: https://twitter.com/saphanaacademy Facebook: https://www.facebook.com/saphanaacademy/ Google+: https://plus.google.com/u/0/111935864030551244982 Github: https://github.com/saphanaacademy
Views: 1302 SAP HANA Academy
How to download all Tweets  from Twitter website
 
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http://www.tothepc.com/?p=15113 Download full tweets archive file for your Twitter account. Click Request for download on Twitter's settings page to get the download link. After download, you can browse whole tweets and RTs archive offline on your computer Visit - http://www.tothepc.com Twitter - http://twitter.com/tothepc Facebook - http://facebook.com/tothepc
Views: 4595 tothepc
Advanced Data Mining with Weka (4.2: Installing with Apache Spark)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 2: Installing with Apache Spark http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/msswhT https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 2246 WekaMOOC
Packet Hacking Village 2017 - MAKE YOUR OWN 802.11AC MONITORING HACKER GADGET BY THOMAS D'OTREPPE
 
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MAKE YOUR OWN 802.11AC MONITORING HACKER GADGET VIVEK RAMACHANDRAN, FOUNDER OF PENTESTER ACADEMY AND SECURITYTUBE.NET THOMAS D'OTREPPE, AUTHOR OF AIRCRACK-NG 802.11ac networks present a significant challenge for scalable packet sniffing and analysis. With projected speeds in the Gigabit range, USB Wi-Fi card based solutions are now obsolete! In this workshop, we will look at how to build a custom monitoring solution for 802.11ac using off the shelf access points and open source software. Our "Hacker Gadget" will address 802.11ac monitoring challenges such as channel bonding, DFS channels, spatial streams and high throughput data rates. We will also look different techniques to do live streaming analysis of 802.11 packets and derive security insights from it! Vivek Ramachandran (Twitter: @securitytube) is the Founder and Chief Trainer at Pentester Academy. He discovered the Caffe Latte attack, broke WEP Cloaking, conceptualized enterprise Wi-Fi Backdoors, created Chellam - the world's first Wi-Fi Firewall and Chigula - a Wi-Fi data mining and IDS framework. He is also the author of multiple five star rated books which have together sold over 13,000+ copies worldwide and have been translated to multiple languages. Vivek started SecurityTube.net in 2007, a YouTube for security which current aggregates the largest collection of security research videos on the web. SecurityTube Training and Pentester Academy now serve thousands of customers from over 90 countries worldwide. Vivek's work on wireless security has been quoted in BBC online, InfoWorld, MacWorld, The Register, IT World Canada etc. places. He has spoken/trained at top conferences around the world including Black Hat USA, Europe and Abu Dhabi, Defcon, Hacktivity, Brucon, Mundo Hacker Day and others. Thomas d'Otreppe (Twitter: @aircrackng) is a wireless security researcher and author of Aircrack-ng, the most popular and complete suite of tools for WiFi network security assessments. He also created OpenWIPS-ng, an open source Wireless Intrusion Prevention System. Thomas is a contributor to the WiFi stack and toolset in Backtrack Linux, which has now become Kali Linux, the de facto top choice Linux distribution for penetration testing and vulnerability assessment across multiple technology domains. He is also known as an author of a pro-active wireless security course which has been delivered to large numbers of IT Security professionals worldwide. Thomas speaks and teaches in the Americas and Europe and is a well-known speaker at DefCon, BlackHat, DerbyCon, SharkFest, Mundo Hacker Day, BruCON and other venues Brought to you by Aries Security - https://www.ariessecurity.com
Views: 426 Wall of Sheep
Advanced Data Mining with Weka (4.3: Using Naive Bayes and JRip)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 3: Using Naive Bayes and JRip http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/msswhT https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 3523 WekaMOOC
Naive Bayes Classifier Tutorial | Naive Bayes Classifier Example | Naive Bayes in R | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Naive Bayes Tutorial video from Edureka will help you understand all the concepts of Naive Bayes classifier, use cases and how it can be used in the industry. This video is ideal for both beginners as well as professionals who want to learn or brush up their concepts in Data Science and Machine Learning through Naive Bayes. Below are the topics covered in this tutorial: 1. What is Machine Learning? 2. Introduction to Classification 3. Classification Algorithms 4. What is Naive Bayes? 5. Use Cases of Naive Bayes 6. Demo – Employee Salary Prediction in R Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #NaiveBayes #NaiveBayesTutorial #DataScienceTraining #Datascience #Edureka How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best."
Views: 37589 edureka!
How to Check Forex Broker Data in MT4
 
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Today i am going to share a method where you can check a broker data of any broker of forex trading. If you can test any EAs or campair two brokers values so you must need to know that broker pervious data. So watch video and check your brokers rates or correct or not. Like My Video: https://youtu.be/7BUG_BEdt_k ** FB Group: https://www.facebook.com/groups/onlinetaleem ** Twitter: https://twitter.com/OnlineTaleem ** InstaGram: https://www.instagram.com/onlinetaleem ** Stumbler: http://www.stumbleupon.com/stumbler/onlinetaleem ** FB Page: https://www.facebook.com/onlinetaleem.net ** Website: http://onlinetaleem.net/ ** Subscribe Our Channel: https://goo.gl/ZszIqV
Views: 349 Online Taleem
Buy Anything For 1 ₹ | How Hackers Tamper Data / HTTP HEADERS Explained
 
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Start Your Hacking Career with my video courses Buy with your Debit/Credit/Netbanking (For Beginners - 14 Days Video Course) Quick Hack Hacking Course: http://imojo.in/681ivb (Best Hacking Course After Quick Hack) Tech Master Hacking Course: http://imojo.in/9srl0c Quick Hack: 299 Rs Tech Master: 299 Rs Or (Ya fir) Buy Hacking Courses With Paytm: http://technicalsagar.in/paytm/ ==================================================================== Hello Friends In this video i will be talking about http headers and get/post method and how hackers use tamper data to shop and buy things on very cheap price, You must be aware of such news when hacker bought airlines tickets and products for only rs 1 and so. I will explain how these things are done. Main motive of this video is to explain how things work so that you can save yourself and gain some knowledge of cybersecurity. My Funny Video On Diwali: https://youtu.be/toEFs1HkmY4 For all updates : LIKE My Facebook Page https://www.facebook.com/technicalsag... Follow Me on Twitter: http://www.twitter.com/iamasagar Follow Abhishek Sagar on Instagram: theabhisheksagar My Setup Camera: http://amzn.to/2xi1POu Collar Mic: http://amzn.to/2gb0J36 Mic: http://amzn.to/2xxBknx Graphics Card: http://amzn.to/2xxLHrH My Second Monitor (Very Affordable): http://amzn.to/2f4swil My Phone: http://amzn.to/2wIqlZD My Lights: http://amzn.to/2eGiG5B ========================================================== My Second Channel For Entertainment: https://youtube.com/SagarKiVani Thanks and Love #TechnicalSagar LIKE | COMMENT | SHARE | SUBSCRIBE ============================================================================================================================================================================================================================================================================== Cartoon - On & On (feat. Daniel Levi) [NCS Release] https://youtu.be/K4DyBUG242c ▽ Follow Cartoon SoundCloud https://soundcloud.com/cartoonbaboon Facebook https://www.facebook.com/cartoondband ▽ Follow Daniel Levi (vocalist) Facebook http://facebook.com/daniellevimusic Website http://daniellevi.eu/
Views: 80 Technical Sagar
How to See  Your Followers' Location on Twitter
 
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We know that social media posting is nothing without analytics; it’s like shooting in the dark. Everything we post has to make sense and has to be addressed to our followers. That’s why it’s important to know who our followers are and where they are located. Whether you are an international brand looking to create marketing campaigns for followers in a specific country, or an artist with performances in different cities who wants to get in touch with those followers - it’s important to know who and WHERE they are coming from. 0:42 - All of the information you need to know about your followers 1:00 - Analyzing your followers’ location: weekly stats 2:23 - Tweepsmap’s interactive follower map 3:39 - Exporting lists of followers 4:19 - Tweepsmap’s Growth/Decline tool Find the Tweepsmap plan that’s right for you: https://tweepsmap.com/signup For more FREE training on the capabilities and efficiency of the Tweepsmap platform, subscribe to our YouTube channel today: https://www.youtube.com/channel/UCgilMVYfZCS9WmgGLnZZBNA Follow @Tweepsmap: Twitter: https://twitter.com/tweepsmap Facebook: https://www.facebook.com/Tweepsmap Tweepsmap Blog: https://tweepsmap.com/blog New to Tweepsmap? Begin exploring the leading intelligence, publishing and listening platform for social media. Get deep analytics of your followers, followers of competitors and trending topics within your target audience so that you can design targeted and cost effective marketing or ad campaigns, and grow your revenue. Use Tweepsmap’s extensive publishing tools to drive engagement and build your community.
Views: 843 Tweepsmap
NIKTO Web vulnerability scanner tool for Kali Linux | WH #9
 
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WH #9 NIKTO Web vulnerability scanner tool for website penetration testing Video Language: Hindi Hello Friends, In this video I will show to you that what is nikto tool? how to scan #website #vulnerabilities using NIKTO in Kali Linux and Parrot SecOS? and don't forget like share & subscribe. Nikto Tool Website: https://cirt.net/Nikto2 NIKTO Tool Github Link https://github.com/sullo/nikto WH series https://www.youtube.com/playlist?list=PL0fjgIGwLMWRC4JXHa6Pzml2Buu-cTigR Watch advance video tutorials- please visit https://techchip.net/products/ ▀▄▀▄▀▄ [ Follow Me on ] ▄▀▄▀▄▀ twitter: https://twitter.com/techchipnet facebook: https://facebook.com/techchip website: www.techchip.net Youtube: https://youtube.com/techchipnet
Views: 14130 TechChip
Advanced Data Mining with Weka (4.4: Map tasks and Reduce tasks)
 
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Advanced Data Mining with Weka: online course from the University of Waikato Class 4 - Lesson 4: Map tasks and Reduce tasks http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/msswhT https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 1249 WekaMOOC
Learn Excel - Sentiment Analysis - Podcast 2062
 
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It is easy to quantify survey data when it is multiple choice You can use a pivot table to figure out what percentage each answer has But what about free-form text answers? These are hard to process if you have hundreds or thousands of them. Sentiment Analysis is a machine-based method for predicting if an answer is positive or negative. Microsoft offers a tool that does Sentiment Analysis in Excel - Azure Machine Learning. Traditional sentiment analysis requires a human to analyze and categorize 5% of the statements. Traditional sentiment analysis is not flexible - you will rebuild the dictionary for each industry. Excel uses MPQA Subjectivity Lexicon (read about that at http://bit. ly/1SRNevt) This generic dictionary includes 5,097 negative and 2,533 positive words Each word is assigned a strong or weak polarity This works great for short sentences, such as Tweets or Facebook posts It can get fooled by double-negatives To install, go to Insert, Excel Store, search for Azure Machine Learning Specify an input range and two blank columns for the output range. The heading for the input range has to match the schema: tweet_text Companion article at: http://sfmagazine.com/post-entry/may-2016-excel-sentiment-analysis/
Views: 3459 MrExcel.com
2015 Twitter Tutorial - How to Create Twitter Collections to Share
 
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2015 Twitter Tutorial - How to Create Twitter Collections to Share Social Media Tips, Tools and Strategies for your business, organization or brand to boost your social status to the maximum level. SUBSCRIBE! Join Smart Office Help Social Media Management: http://twitter.com/smartofficehelp | http://fb.me/smartofficehelp Lifestyle CHANNEL: http://youtube.com/lizforaday TWITTER: http://twitter.com/smartofficehelp FACEBOOK: http://facebook.com/smartofficehelp GOOGLE+: http://google.com/+smartofficehelp
The Connected Vehicle: How Analytics Drives Telematics Value
 
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http://www.sas.com/automotive Learn how SAS' Internet of Things technology is turning mundane telematics trouble codes into real value in the automotive and trucking industries. When everything is connected, we need answers, we need the Analytics of Things. SAS AUTOMOTIVE SOLUTIONS Drive better decisions with the world’s best analytics. SAS has automotive solutions for: * Sales & Marketing * Product & Process Quality * Aftermarket Service * Credit & Finance * Supply & Demand Planning * And more... LEARN MORE ABOUT SAS SOLUTIONS FOR AUTOMOTIVE http://www.sas.com/en_us/industry/automotive.html SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 75,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®. VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 17807 SAS Software
Chinese Name to Structure (CN2S) and Its Application in Chinese Text Mining
 
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Name to Structure (N2S) is a mature English name-to-structure conversion API development by ChemAxon. It is the underlying technology used in ChemAxon's chemical text mining tool D2S (Document to Structure). D2S can extract chemical information from individual file or a document repository system, such as Documentum and SharePoint. To accommodate the fast growing Chinese scientific literature, ChemAxon has recently developed CN2S (Chinese Name to Structure). In this presentation, we will demonstrate how CN2S can convert Chinese chemical names to structures, and its application in Chinese text mining.
Views: 261 ChemAxon
RSA 2017 ▶︎ Hacking Medical Imaging
 
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At RSA 2017 we caught up with Zeev Glozman to discuss his research on how to exploit little known vulnerabilities within medical imaging DICOM (Digital Imaging and Communications in Medicine) files. Glozman discovered this widespread vulnerability that turns medical imaging into an attack vector when patients, doctors and hospitals exchange MRIs, ultrasounds, etc on disks that can contain altered payloads that can trigger remote code execution. Leave us a comment to let us know what you thought of this interesting exploit. SUBSCRIBE to SecureNinjaTV to catch weekly episodes of.. + Hacking Demos + Cybersecurity Discussions + Tech Trade Show Coverage From Around The World If you are in need of Cybersecurity training head over to www.SecureNinja.com for onsite or classroom course options. FOLLOW US: Twitter.com/Secureninja Instagram.com/SecureNinja Facebook.com/SecureNinja Snapchat/ SecureNinja Jon's Channel: https://www.youtube.com/RestofEverest Alicia's Channel: https://www.youtube.com/AMAETV
Views: 1051 SecureNinjaTV
PHP Instagram Downloader Tutorial - 5 - Connection Settings and Access Tokens
 
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Facebook - https://www.facebook.com/TheNewBoston-464114846956315/ GitHub - https://github.com/buckyroberts Google+ - https://plus.google.com/+BuckyRoberts LinkedIn - https://www.linkedin.com/in/buckyroberts reddit - https://www.reddit.com/r/thenewboston/ Support - https://www.patreon.com/thenewboston thenewboston - https://thenewboston.com/ Twitter - https://twitter.com/bucky_roberts
Views: 5932 thenewboston
Introduction to Packet Analysis - Part 2: Network Protocols
 
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Author: Jeremy Druin Twitter: @webpwnized Note: Please help this channel by subscribing and up voting. You can even support us at https://www.youtube.com/user/webpwnized! Description: From the ISSA-KY Network Packet Analysis Workshop, this video introduces the basics of the OSI packet model, application packet model and common network protocols. Later videos will discuss specific protocols such as TCP, IP, UDP and HTTP. Later, packets will be captured into PCAPs which are analyzed with Wireshark and Network Miner. If you would like access to the full course including the lab exercises and walk-through, please consider taking the course at http://ellipsisinfosec.teachable.com/p/introduction-to-network-packet-analysis-and-forensics. Thanks again.
Views: 4474 webpwnized
Hindi- Intrusion Detection Systems IDS and its Types (Network + Host Based)
 
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Intrusion Detection Systems (IDS) and its Types (Network + Host Based) in Hindi Intro An intrusion detection system (IDS) is a device or software application that monitors a network or systems for malicious activity or policy violations. Any detected activity or violation is typically reported either to an administrator or collected centrally using a security information and event management (SIEM) system. A SIEM system combines outputs from multiple sources, and uses alarm filtering techniques to distinguish malicious activity from false alarms. There is a wide spectrum of IDS, varying from antivirus software to hierarchical systems that monitor the traffic of an entire backbone network.[citation needed] The most common classifications are network intrusion detection systems (NIDS) and host-based intrusion detection systems (HIDS). A system that monitors important operating system files is an example of a HIDS, while a system that analyzes incoming network traffic is an example of a NIDS. It is also possible to classify IDS by detection approach: the most well-known variants are signature-based detection (recognizing bad patterns, such as malware) and anomaly-based detection (detecting deviations from a model of "good" traffic, which often relies on machine learning). Some IDS have the ability to respond to detected intrusions. Systems with response capabilities are typically referred to as an intrusion prevention system. Network intrusion detection systems Network intrusion detection systems (NIDS) are placed at a strategic point or points within the network to monitor traffic to and from all devices on the network. It performs an analysis of passing traffic on the entire subnet, and matches the traffic that is passed on the subnets to the library of known attacks. Once an attack is identified, or abnormal behavior is sensed, the alert can be sent to the administrator. An example of an NIDS would be installing it on the subnet where firewalls are located in order to see if someone is trying to break into the firewall. Ideally one would scan all inbound and outbound traffic, however doing so might create a bottleneck that would impair the overall speed of the network. OPNET and NetSim are commonly used tools for simulation network intrusion detection systems. NID Systems are also capable of comparing signatures for similar packets to link and drop harmful detected packets which have a signature matching the records in the NIDS. When we classify the design of the NIDS according to the system interactivity property, there are two types: on-line and off-line NIDS, often referred to as inline and tap mode, respectively. On-line NIDS deals with the network in real time. It analyses the Ethernet packets and applies some rules, to decide if it is an attack or not. Off-line NIDS deals with stored data and passes it through some processes to decide if it is an attack or not. Host intrusion detection systems Host intrusion detection systems (HIDS) run on individual hosts or devices on the network. A HIDS monitors the inbound and outbound packets from the device only and will alert the user or administrator if suspicious activity is detected. It takes a snapshot of existing system files and matches it to the previous snapshot. If the critical system files were modified or deleted, an alert is sent to the administrator to investigate. An example of HIDS usage can be seen on mission critical machines, which are not expected to change their configurations. Intrusion detection systems can also be system-specific using custom tools and honeypots. Find More Info at https://goo.gl/L2XzQg Like Facebook Page https://www.facebook.com/genrontech Follow Twitter Page https://twitter.com/GenronTech Follow Google Pag https://plus.google.com/+Genrontechdotcom Follow Pinterest https://in.pinterest.com/genrontech
Views: 14141 Genron Tech
web application security scanner | WAscan | Kali Linux 2018.1
 
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web application security scanner | WAscan | Kali Linux 2018.1 WAScan ((W)eb (A)pplication (Scan)ner) is a Open Source web application security scanner. It is designed to find various vulnerabilities using "black-box" method, that means it won't study the source code of web applications but will work like a fuzzer, scanning the pages of the deployed web application, extracting links and forms and attacking the scripts, sending payloads and looking for error messages,..etc. WAScan is built on python2.7 and can run on any platform which has a Python environment. Download:https://github.com/m4ll0k/WAScan Features:................... +Fingerprint -Detect Server -Detect Web Frameworks (22) -Check Cookie Security -Check Headers Security -Detect Language (9) -Detect Operating System (OS - 8) -Detect Content Management System (CMS - 6) -Detect Web Application Firewall (WAF - 54) +Attacks -Bash Command Injection (ShellShock) -Blind SQL Injection -SQL Injection via Cookie,Referer and User-Agent Header Value -Cross-Site Scripting (XSS) via Cookie,Referer and User-Agent -Header Value -Buffer Overflow -HTML Code Injection -PHP Code Injection -LDAP Injection -Local File Inclusion (lfi) -OS Commanding -SQL Injection -XPath Injection -Cross Site Scripting (XSS) +Audit -Apache Status -WebDav -PHPInfo -Robots Paths -Cross-Site Tracing (XST) +Bruteforce -Admin Panel -Backdoor (shell) -Backup Dirs -Backup Files -Common Dirs -Common Files +Disclosure -Credit Cards -Emails -Private IP -SSN -Detect Warnings,Fatal Error,...! 📍Installation: $ git clone https://github.com/m4ll0k/WAScan.git wascan $ cd wascan $ pip install -r requirements.txt $ python wascan.py ----------------------------------------------------------------------------------------------- ☑️Subscribe for More Videos: https://goo.gl/MrTQ5r Education Purpose Only !! 🌍Get More Tutorials Here: https://www.patreon.com/theshadowbrokers Follow Me: Face-book: https://goo.gl/ScNuSH Twitter: https://goo.gl/TTYpMR Stumble-upon: https://goo.gl/M5DnF6 Tumber: https://goo.gl/dzuhE9 -The NSA Hackers Thanks !
Views: 2425 The Shadow Brokers
Video Review: Fynch  (Twitter extension for Android)
 
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Rooster App Review S02E27: Fynch (Twitter extension for Android) ----------------------------------------- Description from Google Play: Fynch enhances your Twitter experience by automatically analyzing your timeline for interesting patterns of activity. It is intended to be a tool that decomposes your timeline into smaller sets of tweets that are easier to consume. Fynch is great for identifying extremely high rates of activity, trending topic mentions, and the tweets of less active users in your following list. Keep up with all your friends, and even favorite celebrities, with Fynch's unique data mining technology that compiles your timeline into three kinds of "Fynch's", for easy, organized access. Interested in what one of your Twitter friends has to say? Tap the user's "Fynch", to unveil the group of tweets they have written. Want to go even further? Tap a Tweet that interests you and you will be immediately directed to your Twitter app for the favorite, re-tweet, and reply options. FEATURES: - Automatically analyzes your timeline for interesting patterns of activity. - Carbon fiber holo theme. - Google Now style cards. - Expandable inbox style notifications (Jelly Bean+). - Uses notification priorities (Jelly Bean+). SETTINGS: -Notifications ON/OFF -High Priority Notification -Configurable Tone -Time Analysis Sample Rate -Sensitivity "Stay in-the-know with Fynch!" REQUIREMENTS: - A Twitter account. - The official Twitter app or Falcon Pro if you want to reply to, re-tweet, or favorite a tweet. Google Play link: https://play.google.com/store/apps/details?id=com.rn.fynch&hl=en
Views: 281 appsRooster
Admin Panel Bypass Using No Redirect Add-ons
 
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Admin Panel Bypass Using No Redirect Add-ons::: Dork: admin/index.php .............................................................................................................. Facebook: https://www.facebook.com/fir3.hawk5 ............................................................................................................... YouTube subscribe to channel: https://www.youtube.com/channel/UC1rTCXlWyxfe4WUuFF-rn4A .............................................................................................................. Twitter: https://twitter.com/Fir3_Hawk
Views: 1883 Fir3 Hawk
DEF CON 20 - Ben Toews and Scott Behrens - Rapid Blind SQL Injection Exploitation with BBQSQL
 
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Copy of the slides for this talk are here:https://media.defcon.org/dc-20/presentations/Toews-Behrens/DEFCON-20-Toews-Behrens-BBQSQL.pdf Extras:https://media.defcon.org/dc-20/presentations/Toews-Behrens/Extras.zip Rapid Blind SQL Injection Exploitation with BBQSQL Ben Toews Security Consultant, Neohapsis Scott Behrens Security Consultant, Neohapsis Blind SQL injection can be a pain to exploit. When the available tools work they work well, but when they don't you have to write something custom. This is time-consuming and tedious. This talk will be introducing a new tool called BBQSQL that attempts to address these concerns. This talk will start with a brief discussion of SQL Injection and Blind SQL Injection. It will then segue into a discussion of how BBQSQL can be useful in exploiting these vulnerabilities. This talk will cover how features like evented concurrency and character frequency based searching can greatly improve the performance of a SQL Injection tool. This talk should leave you with enough knowledge to begin using BBQSQL to simplify and speed up your application pentests. Ben Toews is a Security Consultant at Neohapsis where he specializes in application and network pentesting. Previously, Ben has worked as a sysadmin and as a developer. Ben has spoken at Thotcon 0x03 and has been published in HITB Magazine. Ben has a BS in Information Assurance and Security Engineering from DePaul University. Twitter: @mastahyeti http://btoe.ws Scott Behrens is currently employed as a Security Consultant at Neohapsis and an Adjunct Professor at DePaul University. Before Neohapsis, Scott Behrens was an Open Systems Architect for a financial consulting firm, as well as a Network Administrator at Argonne National Laboratories. Scott Behrens' expertise lies in software security assessment, network penetration testing, social engineering, security architecture, and security research. Scott is also the co-developer of NeoPI, a framework to aid in the detection of obfuscated malware. Scott has also presented at Chicago B-sides and has published numerous articles in various security outlets. Scott Behrens has an MS in Network Security from DePaul University. Twitter: @HelloArbit http://www.scottbehrens.com
Views: 642 DEFCONConference
R Data Visualization - Word Clouds and 3D Plots : Constructing a Sunflower Plot | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2rdofNF]. When the density of data increases in a particular region of a plot, it becomes hard to read. So in this video, the sunflower plots are used as variants of scatter plots to display bivariate distribution. • Load the Galton data • Examine the headers and first six observations • Construct a sunflower plot For the latest Application development video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 159 Packt Video
QuickBooks Desktop Client Export
 
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In this tutorial you will learn how to export your client list from QuickBooks desktop so it can be imported into Estimate Rocket. Website: https://www.estimaterocket.com/ Login Page: https://login.estimaterocket.com/ Support: https://support.estimaterocket.com/ Like us on Facebook: https://www.facebook.com/estimaterocket/ Follow us on Twitter: https://twitter.com/estimaterocket
Views: 116 EstimateRocket
Power BI Crtitical Analysis
 
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This is a submission for FIT5154 Introduction to Data Science, as part of the Graduate Diploma of Data Science from Monash University. Link to the Power BI report: https://app.powerbi.com/view?r=eyJrIjoiMTU4Y2IzODYtYTA0YS00MTQyLWFkOWEtNzJhODdlYzU3NmU5IiwidCI6IjVjMTU3Y2ZmLTY3M2QtNDJjZS1iYmFiLTJjZTI3YzM1Y2NiMiIsImMiOjEwfQ%3D%3D
Views: 133 Ellen Boylen
Shimano Tekota LC Meter
 
01:23
Tekota Line Counter (LC) er et skikkelig mesterverk fra Shimano. Ramme, spole og sideplater er produsert i aluminium. Snella har et meget solid og følsomt bremsesystem og en meterteller som er et must i mange fiskesituasjoner. Brukes til sjøfiske, havfiske og trolling. Meget populær i norske farvann. Telleverket vedlikeholdes enkelt med en dråpe olje Den største kveita teamet vårt har tatt inn på den minste i serien, Tekota 600LC, var på hele 145kg! Se video nederst. HAGANE Body 3 A-RB +1 Super Stopper Level Wind System Snellehus / rotor I Diecast aluminium Single Steel power handle Justerbar lengde på sveiv Dartanium Drag Star Drag Spolemateriale i Kaldpresset aluminium Stainless Steel Gear Line Counter meterteller Justerbar Clicker Bøylefeste
Views: 2286 Normark Norway
Accessing Web Content with Alteryx Analytics
 
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See how you can use Alteryx Analytics to access data from a website, then parse the data and prepare it for blending with other data sources.
Views: 7288 Alteryx
Dynamic Malware Analysis D3P18 Actionable Output Yara Lab Bot Classification
 
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Get the class materials to follow along at http://www.opensecuritytraining.info/MalwareDynamicAnalysis.html Follow us on Twitter for class news @OpenSecTraining. The playlist for this class is at: http://bit.ly/YkYmMO This introductory malware dynamic analysis class by Veronica Kovah is dedicated to people who are starting to work on malware analysis or who want to know what kinds of artifacts left by malware can be detected via various tools. The class will be a hands-on class where students can use various tools to look for how malware is: Persisting, Communicating, and Hiding We will achieve the items above by first learning the individual techniques sandboxes utilize. We will show how to capture and record registry, file, network, mutex, API, installation, hooking and other activity undertaken by the malware. We will create fake network responses to deceive malware so that it shows more behavior. We will also talk about how using MITRE's Malware Attribute Enumeration & Characterization (MAEC - pronounced "Mike") standard can help normalize the data obtained manually or from sandboxes, and improve junior malware analysts' reports. The class will additionally discuss how to take malware attributes and turn them into useful detection signatures such as Snort network IDS rules, or YARA signatures. Dynamic analysis should always be an analyst's first approach to discovering malware functionality. But this class will show the instances where dynamic analysis cannot achieve complete analysis, due to malware tricks for instance. So in this class you will learn when you will need to use static analysis, as offered in follow the follow on Introduction to Reverse Engineering and Reverse Engineering Malware classes. During the course students will complete many hands on exercises. Course Objectives: * Understand how to set up a protected dynamic malware analysis environment * Get hands on experience with various malware behavior monitoring tools * Learn the set of malware artifacts an analyst should gather from an analysis * Learn how to trick malware into exhibiting behaviors that only occur under special conditions * Create actionable detection signatures from malware indicators This class is recommended for a later class on malware static analysis. This is so that students understand both techniques, and utilize the technique which gives the quickest answer to a given question.
Enable Power Query add in for excel 2013
 
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Enable Power Query add-in for excel 2013.
Views: 537 Learn 2 Excel