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Download Various Datasets for Hadoop from Websites | Easylearning.guru
 
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In this dataset tutorial video, information to download datasets for analysis is provided. Some of the main points discussed in this video are: • What are datasets and how to download different dataset repository • Step by step procedure to download datasets for data mining • Websites from where you can download datasets • How to analyse downloaded dataset Subscribe to our YouTube channel to watch more interesting and informative videos. Email - [email protected] Phone call - 0124 - 4763660
The Best Way to Prepare a Dataset Easily
 
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In this video, I go over the 3 steps you need to prepare a dataset to be fed into a machine learning model. (selecting the data, processing it, and transforming it). The example I use is preparing a dataset of brain scans to classify whether or not someone is meditating. The challenge for this video is here: https://github.com/llSourcell/prepare_dataset_challenge Carl's winning code: https://github.com/av80r/coaster_racer_coding_challenge Rohan's runner-up code: https://github.com/rhnvrm/universe-coaster-racer-challenge Come join other Wizards in our Slack channel: http://wizards.herokuapp.com/ Dataset sources I talked about: https://github.com/caesar0301/awesome-public-datasets https://www.kaggle.com/datasets http://reddit.com/r/datasets More learning resources: https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-data-science-prepare-data http://machinelearningmastery.com/how-to-prepare-data-for-machine-learning/ https://www.youtube.com/watch?v=kSslGdST2Ms http://freecontent.manning.com/real-world-machine-learning-pre-processing-data-for-modeling/ http://docs.aws.amazon.com/machine-learning/latest/dg/step-1-download-edit-and-upload-data.html http://paginas.fe.up.pt/~ec/files_1112/week_03_Data_Preparation.pdf Please subscribe! And like. And comment. That's what keeps me going. And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 151857 Siraj Raval
Datasets : How to Download?
 
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Datasets : How to Download?
Views: 4738 Social Networks
First time Weka Use : How to create & load data set in Weka : Weka Tutorial # 2
 
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This video will show you how to create and load dataset in weka tool. weather data set excel file https://eric.univ-lyon2.fr/~ricco/tanagra/fichiers/weather.xls
Views: 31447 HowTo
How to Make a Data Science Project with Kaggle (AI Adventures)
 
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It can take a lot of tools to do data science, but Kaggle is a one-stop shop that provides all the tools to share and collaborate on data science projects. In the episode of AI Adventures, Yufeng is joined by Megan Risdal, product lead for datasets at Kaggle. They’ll teach you how to make a data science project with Kaggle, and more! Associated blog post → http://bit.ly/2u18Tyh Get started with Kaggle → https://kaggle.com/datasets Introduction to Kaggle Kernels → http://bit.ly/2z409xm [Dataset] LA County Health Code Violations → http://bit.ly/2MFwyvO [Kernel] Exploring LA County Health Code Violations → http://bit.ly/2KIBz6e Watch more AI Adventures → http://bit.ly/AIAdventures Subscribe to the Google Cloud Platform channel → http://bit.ly/GCloudPlatform
Views: 26170 Google Cloud Platform
Extract Facebook Data and save as CSV
 
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Extract data from the Facebook Graph API using the facepager tool. Much easier for those of us who struggle with API keys ;) . Blog Post: http://davidsherlock.co.uk/using-facepager-find-comments-facebook-page-posts/
Views: 194714 David Sherlock
GEO DataSets
 
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( http://www.abnova.com ) - The Gene Expression Omnibus (GEO) is a public repository that stores original submitter-supplied curated gene expression DataSets. This video shows you how to enter search terms to locate experiments of interest and interpret GEO DataSets results pages. More videos at Abnova http://www.abnova.com
Views: 8686 Abnova
Download Datasets
 
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In this video you will learn how to download videos from http://lock5stat.com/datapage.html and upload them to your Google Drive. I will also review how to compute useful quantities from the downloaded file.
Views: 6688 Phong Le
Hướng dẫn download từ UCI data
 
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Dành cho lớp KTHH05
Views: 2410 Minh Nguyễn
Getting started in scikit-learn with the famous iris dataset
 
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Now that we've set up Python for machine learning, let's get started by loading an example dataset into scikit-learn! We'll explore the famous "iris" dataset, learn some important machine learning terminology, and discuss the four key requirements for working with data in scikit-learn. Download the notebook: https://github.com/justmarkham/scikit-learn-videos Iris dataset: http://archive.ics.uci.edu/ml/datasets/Iris scikit-learn dataset loading utilities: http://scikit-learn.org/stable/datasets/ Fast Numerical Computing with NumPy (slides): https://speakerdeck.com/jakevdp/losing-your-loops-fast-numerical-computing-with-numpy-pycon-2015 Fast Numerical Computing with NumPy (video): https://www.youtube.com/watch?v=EEUXKG97YRw Introduction to NumPy (PDF): http://www.engr.ucsb.edu/~shell/che210d/numpy.pdf WANT TO GET BETTER AT MACHINE LEARNING? HERE ARE YOUR NEXT STEPS: 1) WATCH my scikit-learn video series: https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A 2) SUBSCRIBE for more videos: https://www.youtube.com/dataschool?sub_confirmation=1 3) JOIN "Data School Insiders" to access bonus content: https://www.patreon.com/dataschool 4) ENROLL in my Machine Learning course: https://www.dataschool.io/learn/ 5) LET'S CONNECT! - Newsletter: https://www.dataschool.io/subscribe/ - Twitter: https://twitter.com/justmarkham - Facebook: https://www.facebook.com/DataScienceSchool/ - LinkedIn: https://www.linkedin.com/in/justmarkham/
Views: 139434 Data School
Social Network Datasets
 
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Social Network Datasets
Views: 2913 Social Networks
Data Mining with Weka (1.3: Exploring datasets)
 
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Data Mining with Weka (1.3: Exploring datasets)
Analyzing Public Datasets 2: Finding the Data
 
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In this new series, we'll learn how to access and analyze public datasets resulting from next-generation sequencing techniques such as Illumina and 454. This video shows how to find a sample dataset, upload it to Galaxy, and process it for alignment.
Views: 12035 David Coil
downloading data sets
 
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Views: 242 ProfLMurray
How to do the Titanic Kaggle competition in R - Part 1
 
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As part of submitting to Data Science Dojo's Kaggle competition you need to create a model out of the titanic data set. We will show you how to do this using RStudio. Titanic Data Set: https://www.kaggle.com/c/titanic Download RStudio: https://www.rstudio.com/products/rstu... -- At Data Science Dojo, we're extremely passionate about data science. We've helped educate and train 3600+ employees from over 742 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f6y390 See what our past attendees are saying here: https://hubs.ly/H0f6wND0 -- 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: 48355 Data Science Dojo
Import Data and Analyze with MATLAB
 
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Data are frequently available in text file format. This tutorial reviews how to import data, create trends and custom calculations, and then export the data in text file format from MATLAB. Source code is available from http://apmonitor.com/che263/uploads/Main/matlab_data_analysis.zip
Views: 353768 APMonitor.com
Import Data and Analyze with Python
 
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Python programming language allows sophisticated data analysis and visualization. This tutorial is a basic step-by-step introduction on how to import a text file (CSV), perform simple data analysis, export the results as a text file, and generate a trend. See https://youtu.be/pQv6zMlYJ0A for updated video for Python 3.
Views: 196491 APMonitor.com
KNN using UCI machine learning repository datasets, by S. Han
 
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A short Python tutorial for KNN, by Sooan Han (Creative Technology Management, Underwood International College, Yonsei University, South Korea)
Views: 258 Kee Heon Lee
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 436440 Brandon Weinberg
Introduction to Data Science with R - Data Analysis Part 1
 
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Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 881562 David Langer
Building dataset - p.4 Data Analysis with Python and Pandas Tutorial
 
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In this part of Data Analysis with Python and Pandas tutorial series, we're going to expand things a bit. Let's consider that we're multi-billionaires, or multi-millionaires, but it's more fun to be billionaires, and we're trying to diversify our portfolio as much as possible. We want to have all types of asset classes, so we've got stocks, bonds, maybe a money market account, and now we're looking to get into real estate to be solid. You've all seen the commercials right? You buy a CD for $60, attend some $500 seminar, and you're set to start making your 6 figure at a time investments into property, right? Okay, maybe not, but we definitely want to do some research and have some sort of strategy for buying real estate. So, what governs the prices of homes, and do we need to do the research to find this out? Generally, no, you don't really need to do that digging, we know the factors. The factors for home prices are governed by: The economy, interest rates, and demographics. These are the three major influences in general for real estate value. Now, of course, if you're buying land, various other things matter, how level is it, are we going to need to do some work to the land before we can actually lay foundation, how is drainage etc. If there is a house, then we have even more factors, like the roof, windows, heating/AC, floors, foundation, and so on. We can begin to consider these factors later, but first we'll start at the macro level. You will see how quickly our data sets inflate here as it is, it'll blow up fast. So, our first step is to just collect the data. Quandl still represents a great place to start, but this time let's automate the data grabbing. We're going to pull housing data for the 50 states first, but then we stand to try to gather other data as well. We definitely dont want to be manually pulling this data. First, if you do not already have an account, you need to get one. This will give you an API key and unlimited API requests to the free data, which is awesome. Once you create an account, go to your account / me, whatever they are calling it at the time, and then find the section marked API key. That's your key, which you will need. Next, we want to grab the Quandl module. We really don't need the module to make requests at all, but it's a very small module, and the size is worth the slight ease it gives us, so might as well. Open up your terminal/cmd.exe and do pip install quandl (again, remember to specify the full path to pip if pip is not recognized). Next, we're ready to rumble, open up a new editor. http://pythonprogramming.net https://twitter.com/sentdex
Views: 95593 sentdex
How to use Kaggle ?
 
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Learn how to use Kaggle. We discuss about Competitions, Discussions, Evaluation, Submissions, Kaggle Kernels and much more.. Deep Learning book : https://amzn.to/2FTO77C Connect with us on Twitter: https://twitter.com/aijournalyt Please support me on Patreon : https://patreon.com/aijournal
Views: 27017 AI Journal
Import Data, Copy Data from Excel to R CSV & TXT Files | R Tutorial 1.5 |MarinStatsLectures
 
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Import Data, Copy Data from Excel (or other spreadsheets) to R CSV & TXT Files; Practice with Dataset: https://goo.gl/tJj5XG More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to Import CSV data into R or How to Import TXT files into R from Excel or other spreadsheets using function in R ▶︎How to import CSV data into R? We will be using "read.table" function to import comma separated data into R ▶︎ How to import txt data file into R? You will learn to use "read.delim" function to import the data to R ▶︎ In addition, you will also learn to use "file.choose" argument for file location, "header" argument to let R know the data has headers or variable names and "sep" argument to let R know how the data values are separated. ▶︎▶︎Download the dataset here: https://statslectures.com/r-stats-datasets ▶︎▶︎Watch More: ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH ▶︎Getting Started with R: https://bit.ly/2PkTneg ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ◼︎ Table of Content 0:00:17 What are the two main file types for saving a data file 0:00:36 How to save an Excel file as a CSV file (comma-separated value) 0:01:10 How to open a CSV data file in Excel 0:01:20 How to open a CSV file in text editor 0:01:36 How to import CSV file into R? using read.csv function 0:01:44 How to access the help menu for different commands/functions in R 0:02:04 How to specify file location in R? using file.choose argument on read.csv function 0:02:31 How to let R know data has headers or variable names? using the header argument on read.csv function 0:03:22 How to import CSV file into R? using read.table function 0:03:38 How to specify the file location in R for read.table function? using file.choose argument 0:03:46 How to specify in R know how the data values are separated? the "sep" argument on read.table function 0:04:10 How to save a file in Excel as tab-delimited text (TXT) file 0:04:50 How to open a tab-delimited (.TXT) data file in a text editor 0:05:07 How to open a tab-delimited (.TXT) data file in excel 0:05:20 How to import tab-delimited (.TXT) data file into R? using read.delim function 0:05:44 How to to specify the file path for read.delim function in R? using file.choose argument 0:06:06 How to import tab-delimited (.TXT) data file into R? using read.table function 0:06:23 How to specify that the data has headers or variable in R?Using header argument on read.table function This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://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 and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) The #RTutorial is created by #marinstatslectures to support the statistics course (SPPH400 #IntroductoryStatistics) at The University of British Columbia(UBC) although we make all videos available to the everyone everywhere for free! Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Partitioning data into training and validation datasets using R
 
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Link to download data file: https://drive.google.com/open?id=0B5W8CO0Gb2GGUVNyZ1JqMW1NZjA Includes example of data partition or data splitting with R. - Shows steps for reading CSV file into R. - Illustrates developing linear regression model using training data and then making predictions using validation data set in r. - Discusses regression coefficients - Provides application example using an automobile warranty claims dataset R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 26891 Bharatendra Rai
Text mining 2
 
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In this video, we are going to continue to use Text Mining widgets in Orange. In order to download the datasets please go to: https://github.com/RezaKatebi/Crash-course-in-Object-Oriented-Programming-with-Python
Views: 117 DataWiz
Importing , Checking and Working with Data in R | R Tutorial 1.7 | MarinStatsLectures
 
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Importing Data, Checking the Imported Data and Working With Data in R; Dataset: https://goo.gl/tJj5XG More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to import a datasets into R , How to make sure data was imported correctly into R and How to begin to work with the imported data in R. ▶︎We will learn to use read.table function (which reads a file in table format and creates a data frame from it, with cases corresponding to lines and variables to fields in the file), and some of the arguments such as header argument and sep argument. ▶︎We will learn to use file.choose function to choose a file interactively ▶︎We will discuss how to use Menu options in RStudio to import data into R ▶︎and how to check the imported data to make sure it was imported correctly into R using the dim function to retrieve dimension of an object and let you know the number of rows and columns of the imported data, the head function in R (head() function), which returns the first or last parts of a vector, matrix, table, data frame and will let you see the first several rows of the data, the tail function in R (tail() function) to see the last several rows of the data in R, the double square brackets in R to subset data (brackets lets you select or subset data from a vector, matrix, array, list or data frame) , and the names function in R to get the names of an object in R. ▶︎▶︎ Download the dataset here: https://statslectures.com/r-stats-datasets ▶︎▶︎Watch More ▶︎Export Data from R (CSV , TXT and other formats): https://bit.ly/2PWS84w ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability Distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate Analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH ◼︎ Topics in the video: 0:00:07 How to read a dataset into R using read.table function 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 function 0:03:15 How to use Menu options in R Studio to import data into R 0:05:23 How to prepare the Excel data for importing into R 0:06:15 How to know the dimensions (the number of rows and columns) of the data in R using the dim function 0:06:35 How to see the first several rows of the data using the head command in R 0:06:45 How to see the last several rows of the data in R using the tail function 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 function This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://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 and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) The #RTutorial is created by #marinstatslectures to support the statistics course (SPPH400 #IntroductoryStatistics) at The University of British Columbia(UBC) although we make all videos available to the everyone everywhere for free! Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
How to prepare panel data in stata and make panel data regression in Stata
 
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This video is dedicated for anyone of you who want to utilize stata to make panel data analysis, the presentation is quick and fast, and to the point! If you want to get the sample xls file for this calculation, please download from my blog in this address https://goo.gl/xnRqgR. Together there you also can see the script of these stata codes or you can also see from the description below. Happy learning! The code for this paneldata preparation in stata is // To re group into numeric the variable parameter egen (proposed variable) = group(the existing variable as a parameter) in this example egen countrynum = group(A) // To check whether the data is fit with the countrynum list A countrynum in 1/10, sepby (A) // To prepare based on the group of parameter xtset (variable of group) xtset countrynum // To set the group yearly xtset countrynum (the yearly variable), yearly xtset countrynum B, yearly // to regres this panel data xtreg (dependent variable) (independet variable and the rest) And guys if you want to get more stata video from me, please dont forget to subscribe! visit my site : https://notafra.id or mail me at : [email protected]
Views: 152122 quickworld
Testing and Training of Data Set Using Weka
 
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how to train and test data in weka data mining using csv file
Views: 11281 Tutorial Spot
Handling Class Imbalance Problem in R: Improving Predictive Model Performance
 
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Provides steps for carrying handling class imbalance problem when developing classification and prediction models Download R file: https://goo.gl/ns7zNm data: https://goo.gl/d5JFtq Includes, - What is Class Imbalance Problem? - Data partitioning - Data for developing prediction model - Developing prediction model - Predictive model evaluation - Confusion matrix, - Accuracy, sensitivity, and specificity - Oversampling, undersampling, synthetic sampling using random over sampling examples predictive models are important machine learning and statistical tools related to analyzing big data or working in data science field. R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 11590 Bharatendra Rai
Retrieve and analyze a gene expression data set from NCBI GEO in R
 
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R script is available at: https://github.com/hongqin/RCompBio/blob/master/ncbigeo/ncbiGEO2012Nov14-demo-youtube.R SBIO386, Spelman College, Fall 2012
Views: 22275 Hong Qin
Rattle Tutorial - How to Open The Sample Weather Dataset in Rattle
 
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This is a quick tutorial on how to open the sample weather.csv dataset in Rattle. This weather dataset is very helpful in learning basic R and Data Mining concepts from books and guides etc. If you don't have rattle make sure you get it by following the official set-up guide here: http://rattle.togaware.com/rattle-install-mac.html (For Mac) Please drop a comment if you want more tutorial in R, Rattle or Data mining and the required area.
Views: 1494 Spellogram
Discretization Algorithm, Data Analytics, KDD, Data Processing
 
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For this video, I will be talking about one of the algorithms used to discretize datasets. Discretizing a dataset is the act of reducing the number of discrete values so that it can be more easily analyzed. This method uses heuristics and discernibility formulas.
Views: 2959 Laurel Powell
SiilatsFinancePart2 Stock Data into Excel.mp4
 
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Financial Data Mining, Part 1 -- Portfolio Management in Microsoft SQL, Data mining with Excel Keith Siilats, 2/4/2012 CS246 Mining of Massive Datasets 1. Download Microsoft VHD for Mac/Windows/Unix http://www.microsoft.com/download/en/details.aspx?id=26113 2. Download VirtualBox and configure it for HyperV http://dynamicsnavax.blogspot.com/2011/04/how-to-run-ax2012-hyperv-on-virtualbox.html 3. Start your VHD and log in with Username Administrator Password [email protected] 4. Install Guest additions from VirtualBox Menu 5. Install shared folders 6. When the 10 day trial period finishes you can rearm up to 4 times a. Click Start, and then click Command Prompt. b. To reset the activation period, type slmgr.vbs --rearm, and then press ENTER. 7. Install Office http://technet.microsoft.com/en-us/evalcenter/ee390818 8. Get some stock data. Key is to get both sector and market cap info, sp500 is the largest 500 companies a. http://www.stockmarketsreview.com/companies_sp500/ b. http://www.cboe.com/products/snp500.aspx 9. Sign up with www.tdameritrade.com It will take you 3 days to sign up and you will get $500. You will see in the video how to export sector data from tdameritrade, it's easier than using the links above. 10. Get an excel macro to download latest prices. You need excel to clean up all the junk prices. Going through text files is no fun. Hoping that machine learning algorithms know how to deal with rubbish data is optimistic. http://code.google.com/p/finance-data-to-excel/ 11. Install Analysis Server samples http://msftdbprodsamples.codeplex.com/wikipage?title=Installing%20SQL%20Server%202008R2%20Databases See how Microsoft does basket analysis, recommendations and all the other algorithms we have covered in class (hint, it's a lot of point and click and very little code). 12. Watch the video on how to create a VBA script to generate data and export it to SQL server (this is the Map step). In practice you will have multiple pricing servers running complex derivative pricing monte carlos and clustered sql server over several machines with hot backup. If you would like to build a machine like this instructions are http://www.tpc.org/tpcc/results/tpcc_price_perf_results.asp Microsoft Analysis server will work with any SQL source including Oracle. 13. In class we will create a custom portfolio management cube. This is the Reduce step, but its kind of a universal reduce. Once you have the cube you connect to it from Excel Pivot Table and can create any Reduce real time. Tutorial on PivotTables http://www.timeatlas.com/5_minute_tips/chunkers/learn_to_use_pivot_tables_in_excel_2007_to_organize_data 14. Here is a tutorial connecting excel to sql server http://newtech.about.com/od/tutorials/ss/How-To-Configure-Excel-2010-Pivot-Table-For-Business-Intelligence.htm 15. Here is a tutorial how to connect Excel to the Analysis Server http://blogs.office.com/b/microsoft-excel/archive/2008/08/28/using-excel-excel-services-with-sql-server-analysis-services-2008.aspx 16. In the second part I will show you how to create cubes on tick data (trades and quotes) and do high frequency trading.
Views: 1110 siilats
Data Partition and Oversampling in the R Software Example Tutorial
 
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1. Download the example data set: fitnessAppLog.csv https://drive.google.com/open?id=0Bz9Gf6y-6XtTczZ2WnhIWHJpRHc 2. Data Partition, Oversampling in the R Software Example Code: https://drive.google.com/open?id=13_EeM3neRu1QDSYx6myZoTQuEx7IHB8j
Views: 1473 The Data Science Show
Project: download data
 
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Part of a series of tutorials on how to setup a PsyToolkit project
Views: 536 Psy Toolkit
KDD99 Data Set Analysis
 
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Analyze KDD99 data set by Sean Han
Views: 3368 Xiao Han
Data Science & Machine Learning - KNN Classification - DIY- 21 -of-50
 
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Data Science & Machine Learning - KNN Classification - DIY- 21 -of-50 Do it yourself Tutorial by Bharati DW Consultancy cell: +1-562-646-6746 (Cell & Whatsapp) email: [email protected] website: http://bharaticonsultancy.in/ Google Drive- https://drive.google.com/open?id=0ByQlW_DfZdxHeVBtTXllR0ZNcEU K – Nearest Neighbors (K-NN) Get the data from Balance Scale Data Set. Attribute Information: Class Name: 3 (L, B, R) Left-Weight: 5 (1, 2, 3, 4, 5) Left-Distance: 5 (1, 2, 3, 4, 5) Right-Weight: 5 (1, 2, 3, 4, 5) Right-Distance: 5 (1, 2, 3, 4, 5) http://archive.ics.uci.edu/ml/datasets/Balance+Scale Citation Policy: If you publish material based on databases obtained from this repository, then, in your acknowledgements, please note the assistance you received by using this repository. This will help others to obtain the same data sets and replicate your experiments. We suggest the following pseudo-APA reference format for referring to this repository: Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science. Here is a BiBTeX citation as well: @misc{Lichman:2013 , author = "M. Lichman", year = "2013", title = "{UCI} Machine Learning Repository", url = "http://archive.ics.uci.edu/ml", institution = "University of California, Irvine, School of Information and Computer Sciences" } Data Science & Machine Learning - Getting Started - DIY- 1 -of-50 Data Science & Machine Learning - R Data Structures - DIY- 2 -of-50 Data Science & Machine Learning - R Data Structures - Factors - DIY- 3 -of-50 Data Science & Machine Learning - R Data Structures - List & Matrices - DIY- 4 -of-50 Data Science & Machine Learning - R Data Structures - Data Frames - DIY- 5 -of-50 Data Science & Machine Learning - Frequently used R commands - DIY- 6 -of-50 Data Science & Machine Learning - Frequently used R commands contd - DIY- 7 -of-50 Data Science & Machine Learning - Installing RStudio- DIY- 8 -of-50 Data Science & Machine Learning - R Data Visualization Basics - DIY- 9 -of-50 Data Science & Machine Learning - Linear Regression Model - DIY- 10(a) -of-50 Data Science & Machine Learning - Linear Regression Model - DIY- 10(b) -of-50 Data Science & Machine Learning - Multiple Linear Regression Model - DIY- 11 -of-50 Data Science & Machine Learning - Evaluate Model Performance - DIY- 12 -of-50 Data Science & Machine Learning - RMSE & R-Squared - DIY- 13 -of-50 Data Science & Machine Learning - Numeric Predictions using Regression Trees - DIY- 14 -of-50 Data Science & Machine Learning - Regression Decision Trees contd - DIY- 15 -of-50 Data Science & Machine Learning - Method Types in Regression Trees - DIY- 16 -of-50 Data Science & Machine Learning - Real Time Project 1 - DIY- 17 -of-50 Data Science & Machine Learning - KNN Classification - DIY- 21 -of-50 Machine learning, data science, R programming, Deep Learning, Regression, Neural Network, R Data Structures, Data Frame, RMSE & R-Squared, Regression Trees, Decision Trees, Real-time scenario, KNN
QUARRY Site Survey Sample Data Pix4D
 
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Pix4D Sample Dataset Video Flythrough for a Quarry mining Site. The sample Dataset can be downloaded here: https://support.pix4d.com/hc/en-us/articles/202561419-Example-Datasets-Available-for-Download-Quarry#gsc.tab=0 Google Maps Tiles KML Mapbox Contour Lines 3D PDF General project information Project Location Switzerland Average Ground Sampling Distance (GSD) 8.78 cm / 3.46 in Area covered 0.5776 km2 / 57.7565 ha / 0.223 sq. mi. / 142.79 acres Output coordinate system WGS84 / UTM zone 32N Vertical Coordinate System: Geoid Height Above WGS 84 Ellipsoid = 0 meters Image acquisition UAV swinglet CAM (senseFly) Image acquisition plan 1 flight, grid flight plan Camera Canon IXUS 220HS (RGB) Images Number of images 127 Image size 4000x3000 Image geolocation coordinate system WGS84 GCPs Number of GCPs 7 3D GCPs GCPs coordinate system WGS84 Download and project files The dataset can be downloaded here. The downloaded folder contains the following files and folders: images: RGB images in JPG format inputs/gcp_overview: images that help to identify each GCPs inputs/gcpPositionsLatLongAlt.csv: GCP input geolocation file. example_quarry.p4d: project file that can be opened in Pix4Dmapper. Follow Ridgeline Mapping & Surveying updates here: http://www.ridgelinemapping.com/news/
Views: 1444 Brandon Cary
K-Means Clustering - Methods using Scikit-learn in Python - Tutorial 23 in Jupyter Notebook
 
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In this tutorial on Python for Data Science, you will learn about how to do K-means clustering/Methods using pandas, scipy, numpy and Scikit-learn libraries in Jupyter notebook. This is the 23th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist "the sexiest job of the 21st century." Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We'll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets Download Link for Cars Data Set: https://www.4shared.com/s/fWRwKoPDaei Download Link for Enrollment Forecast: https://www.4shared.com/s/fz7QqHUivca Download Link for Iris Data Set: https://www.4shared.com/s/f2LIihSMUei https://www.4shared.com/s/fpnGCDSl0ei Download Link for Snow Inventory: https://www.4shared.com/s/fjUlUogqqei Download Link for Super Store Sales: https://www.4shared.com/s/f58VakVuFca Download Link for States: https://www.4shared.com/s/fvepo3gOAei Download Link for Spam-base Data Base: https://www.4shared.com/s/fq6ImfShUca Download Link for Parsed Data: https://www.4shared.com/s/fFVxFjzm_ca Download Link for HTML File: https://www.4shared.com/s/ftPVgKp2Lca
Views: 17706 TheEngineeringWorld
LAS Data Download using R:
 
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download R at https://cran.r-project.org/bin/windows/base/ download RStudio at https://www.rstudio.com/products/rstudio/download3/
Views: 351 Geo Friday
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: 72056 Skillshare
Scaling and Distribution of Data Using Scikit learn in Python - Tutorial 16 Jupyter Notebook
 
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In this Python for data science tutorial, you will learn how to scale your data and data-set distribution in python using scikit learn preprocessing. How to transform your data using scikit-learn in jupyter notebook. This is the 16th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist "the sexiest job of the 21st century." Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We'll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets. Download Link for Cars Data Set: https://www.4shared.com/s/fWRwKoPDaei Download Link for Enrollment Forecast: https://www.4shared.com/s/fz7QqHUivca Download Link for Iris Data Set: https://www.4shared.com/s/f2LIihSMUei https://www.4shared.com/s/fpnGCDSl0ei Download Link for Snow Inventory: https://www.4shared.com/s/fjUlUogqqei Download Link for Super Store Sales: https://www.4shared.com/s/f58VakVuFca Download Link for States: https://www.4shared.com/s/fvepo3gOAei Download Link for Spam-base Data Base: https://www.4shared.com/s/fq6ImfShUca Download Link for Parsed Data: https://www.4shared.com/s/fFVxFjzm_ca Download Link for HTML File: https://www.4shared.com/s/ftPVgKp2Lca
Views: 2064 TheEngineeringWorld
Adam Dataset & Storage (HD)
 
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In this video, I introduce the UCI Machine Learning Repository's wine quality dataset . I talk about the tasks that we will do with this dataset. I walk you through downloading the datasets, storing them and launching your Jupyter Notebook in your project folder. Note: You may have to adjust the visual on the gear in the right lower corner of the video by clicking on the gear and adjusting it HD (1080) resolution.
Views: 24 Adam Morris
My First Kaggle Submission
 
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To prepare you for Data Science Dojo's day two homework we will explain what Kaggle is and show you how to create a Kaggle account and submit your model to the Kaggle competition. Titanic Data Set: https://www.kaggle.com/c/titanic -- At Data Science Dojo, we're extremely passionate about data science. We've helped educate and train 3600+ employees from over 742 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f6y0L0 See what our past attendees are saying here: https://hubs.ly/H0f6wN00 -- 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: 42445 Data Science Dojo
weka - data mining algorithm  (steps to run it)
 
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An introduction on weka software and url to download it. It also contains pre-processing step for the data set and number of data mining algorithms to run with. It is a basic video on how to use weka software.
Views: 348 Akshay Jain
Explaining Clustering in Weka
 
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Clustering in Weka with the help of air quality data set You can download weka from : https://sourceforge.net/projects/weka/ the data set can be found on: https://data.gov.in/
Views: 1500 Aditi
Breast Cancer Diagnosis with Artificial Neural Network
 
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Building, training, exporting and embedding an artificial neural network for use in a custom application for diagnosing cancer in breast tissue samples. Using patient data samples from UCI Machine Learning Repository for research. The resulting application and AI builder are available for download. Send email to [email protected] to request. Or visit tinmansystems.com/aibuilder
Views: 70591 TinMan Systems
Naive Bayes Classifier - Multinomial Bernoulli Gaussian Using Sklearn in Python - Tutorial 32
 
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In this Python for Data Science tutorial, You will learn about Naive Bayes classifier (Multinomial Bernoulli Gaussian) using scikit learn and Urllib in Python to how to detect Spam using Jupyter Notebook. Multinomial Naive Bayes Classifier Bernoulli Naive Bayes Classifier Gaussian Naive Bayes Classifier This is the 32th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist "the sexiest job of the 21st century." Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We'll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets. Download Link for Cars Data Set: https://www.4shared.com/s/fWRwKoPDaei Download Link for Enrollment Forecast: https://www.4shared.com/s/fz7QqHUivca Download Link for Iris Data Set: https://www.4shared.com/s/f2LIihSMUei https://www.4shared.com/s/fpnGCDSl0ei Download Link for Snow Inventory: https://www.4shared.com/s/fjUlUogqqei Download Link for Super Store Sales: https://www.4shared.com/s/f58VakVuFca Download Link for States: https://www.4shared.com/s/fvepo3gOAei Download Link for Spam-base Data Base: https://www.4shared.com/s/fq6ImfShUca Download Link for Parsed Data: https://www.4shared.com/s/fFVxFjzm_ca Download Link for HTML File: https://www.4shared.com/s/ftPVgKp2Lca
Views: 16511 TheEngineeringWorld
Importing A Dataset Into R-Studio
 
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Please watch at a higher resolution and full screen as to capture the details. Learn how to import a text file (dataset) into R-Studio! Covers import, attach(), and detach().
Views: 46960 PortableProfessor

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