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Search results “Data preprocessing algorithm in data mining”
Data Preprocessing
 
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Project Name: Learning by Doing (LBD) based course content development Project Investigator: Prof Sandhya Kode
Views: 40410 Vidya-mitra
Data Preprocessing Steps for Machine Learning & Data analytics
 
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#Pandas #DataPreProcessing #MachineLearning #DataAnalytics #DataScience Data Preprocessing is an important factor in deciding the accuracy of your Machine Learning model. In this tutorial, we learn why Feature Selection , Feature Extraction, Dimentionality Reduction are important. We also learn about the famous methods which can be used for the purpose. Data Preprocessing is a very important step in Data Analytics which is ignored by many. To make your models accurate you have to ensure proper preprocessing as the Machine Learning model is highly dependent on data. For all Ipython notebooks, used in this series : https://github.com/shreyans29/thesemicolon Facebook : https://www.facebook.com/thesemicolon.code Support us on Patreon : https://www.patreon.com/thesemicolon Check out the machine learning, deep learning and developer products USA: https://www.amazon.com/shop/thesemicolon India: https://www.amazon.in/shop/thesemicolon
Views: 17874 The Semicolon
Data Preprocessing
 
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About Data Preprocessing and steps of Preprocessing
Views: 9480 Dr.Anamika Bhargava
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: 175262 Rushdi Shams
Data Preprocessing 2
 
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Project Name: e-Content generation and delivery management for student –Centric learning Project Investigator:Prof. D V L N Somayajulu
Views: 6084 Vidya-mitra
Data Analytics: Week 3 : Data Preprocessing
 
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This is your week 3 lecture. Enjoy!
Views: 19519 Paul Kennedy
Introduction to Data Mining: Data Cleaning
 
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In this Data Mining Fundamentals tutorial, we introduce Data Preprocessing, known as data cleaning, and the different strategies used to tackle it. There are many strategies for data preprocessing, and because data science is such a heterogeneous field, none of these strategies are strictly independent. -- Learn more about Data Science Dojo here: https://hubs.ly/H0hCnFR0 Watch the latest video tutorials here: https://hubs.ly/H0hCnh80 See what our past attendees are saying here: https://hubs.ly/H0hCnG20 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 830 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 10727 Data Science Dojo
Data Pre processing
 
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For more see: http://shishirshakya.blogspot.com/2015/08/data-pre-processing.html
Views: 2506 Shishir Shakya
Data Preprocessing Tutorial
 
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It is easy to preprocess data in Excel with the help of PrimaXL, an add-in software. Amazon: https://www.amazon.com/dp/B077G8CTSR (10$ Coupon included) Facebook : https://www.facebook.com/fianresearch/ Free trial: http://www.fianresearch.com/eng_index.php Purchase license : https://sites.fastspring.com/fianresearch/instant/primaxllicensekeyv2015a
Views: 3735 FIAN Research
Introduction to Data Mining: Types of Sampling
 
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In this Data Mining Fundamentals tutorial, we discuss the different types of sampling for data preprocessing, such as random sampling, stratified sampling, sampling without and with replacement. We will also dive into the issues of sample size, and how that can effect your sampling. -- Learn more about Data Science Dojo here: https://hubs.ly/H0hCnRz0 Watch the latest video tutorials here: https://hubs.ly/H0hCnrN0 See what our past attendees are saying here: https://hubs.ly/H0hCnRN0 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 830 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 7736 Data Science Dojo
Data Preprocessing
 
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This video explains about various methods for data preprocessing and data cleaning
Views: 8405 Sunil Kumar Talluri
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 Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 197310 Siraj Raval
Data Cleaning Process Steps / Phases [Data Mining] Easiest Explanation Ever (Hindi)
 
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📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 27821 5 Minutes Engineering
What is Data Preprocessing in Data Mining Lecture 2 in Urdu/Hindi
 
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what is data preprocessing?
Views: 6587 Focus Group
Data Preprocessing in Data Mining Part one
 
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https://www.facebook.com/Pshtiwan.M.Aziz
Views: 393 Pshtiwan Aziz
Data Preprocessing
 
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Data Preprocessing using Rapidminer The steps undertaken are : 1. Handling missing values 2. Binning 3. Sampling 4. Normalization 5. Correlation Determination
Data mining - Preprocess with Orange
 
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handle for missing value :)
Views: 203 Abdul Raffi
Sampling Techniques [Data Mining](HINDI)
 
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📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 14490 5 Minutes Engineering
Binning | Binning Method | Binning Algorithm | Binning In Data Mining
 
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Binning |Binning Method | Binning Algorithm | Binning In Data Mining ************************************************ the binding of isaac, binning , binnington, equal width binning, binning method, binning algorithm, bin data in r, bin data in excel, binning in excel, binning in data mining, data mining, data mining techniques, data mining tutorial, data mining algorithms, data mining course, data mining excel, r data minin, python data mining, Please Subscribe My Channel
Views: 18137 Learning With Mahamud
Introduction to Data Mining Data Preprocessing for Machine Learning
 
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Machine learning and artificial intelligence helping us in every field. In this tutorial we are going to talk about basics of machine learning. you may ask question in comment about machine learning
Views: 182 RNS Solutions
Data Mining Preprocessing in Jupyter Notebook with Python
 
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Data Mining Preprocessing in Jupyter Notebook with Python using Pandas, Numpy and a Baseball dataset.
Views: 557 D Thomas
Data Preprocessing
 
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In this video i discussed data pre-processing techniques. #datamining #preprocessing #kdd Data mining tutorial in hindi Weka tutorial Data mining tutorial
Views: 425 yaachana bhawsar
Text Classification using Machine Learning : Part 1 - Preprocessing the data
 
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Join me as I build a spam filtering bot using Python and Scikit-learn. In this video, we are going to preprocess some data to make it suitable to train a model on. Code is optimised for Python 2. Download the dataset here: http://www.aueb.gr/users/ion/data/enron-spam/preprocessed/enron1.tar.gz Part 2: https://youtu.be/6Wd1C0-3RXM Entire code available here: https://gist.github.com/SouravJohar/bcbbad0d0b7e881cd0dca3481e32381f
Views: 22032 Sourav Johar
Lecture 5 - Data Preprocessing and Data Mining
 
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This week, Daniel and Saksham talks about how to prepare and preprocess your data before you place it in a machine learning algorithm. We mention topics like continuous and categorical imputation, dummification, categorisation, and much more. Presenters: Daniel, Saksham
Data Mining using R | Data Mining Tutorial for Beginners | R Tutorial for Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R tutorial on "Data Mining using R" will help you understand the core concepts of Data Mining comprehensively. This tutorial will also comprise of a case study using R, where you'll apply data mining operations on a real life data-set and extract information from it. Following are the topics which will be covered in the session: 1. Why Data Mining? 2. What is Data Mining 3. Knowledge Discovery in Database 4. Data Mining Tasks 5. Programming Languages for Data Mining 6. Case study using 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 #LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience 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 For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Website: https://www.edureka.co/data-science 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. " Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 81034 edureka!
Machine Learning - Part 1 - Data Preprocessing
 
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This is the Chapter 1(Data Preprocessing) on Machine Learning . This is the first step when the user wants to makes a ML model. All the essential codes are given in my Github repository. code repository : https://github.com/harshitahluwalia7895/Machine-Learning-Course topics we have covered : 1. How to get the Dataset 2.How to load the Dataset 3.Handling Missing Values 4.Handling the Categorical Data via Dummy Variables follow me on the following networks to get connected with me Github : https://github.com/harshitahluwalia7895 Linkedin : https://www.linkedin.com/in/harshit-ahluwalia-4b1153141/ Twitter : https://twitter.com/Harshit9105 Whatsapp Group : https://lnkd.in/fp5jQeQ if you are a Machine Learning enthusiast then this is for you #100daysofmlcode repo : https://github.com/harshitahluwalia7895/100DaysOfMLCode
Views: 2360 Harshit Ahluwalia
Data Preprocessing for Machine Learning Using MATLAB!
 
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Get The Complete MATLAB Course Bundle for 1 on 1 help! https://josephdelgadillo.com/product/matlab-course-bundle/ Enroll in the FREE course! https://uthena.com/courses/matlab?ref=744aff This course is for you if you want to fully equip yourself with the art of applied machine learning using MATLAB. We will apply the most commonly used data preprocessing techniques without having to learn all the complicated maths. Time Stamps: 00:35 Introduction to the course 05:00 Introduction to MATLAB 13:27 Importing a data-set into MATLAB 21:01 Deletion strategies 29:43 Using mean and mode 40:26 Using a special value 47:25 Class specific mode and mean 1:00:13 Random value imputation Web - https://josephdelgadillo.com Subscribe - https://bit.ly/SubscribeJTD Facebook - https://www.facebook.com/delgadillojt Discord - https://discord.gg/EbcQFrg Instagram - https://www.instagram.com/jo3potato #MATLAB #MachineLearning #DataScience
Views: 3298 Joseph Delgadillo
Weka Tutorial 06: Discretization (Data Preprocessing)
 
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An important feature of Weka is Discretization where you group your feature values into a defined set of interval values. Experiments showed that algorithms like Naive Bayes works well with discretized feature values
Views: 61514 Rushdi Shams
Data pre processing – 1 Summarization and Cleaning Methods
 
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Project Name: e-Content generation and delivery management for student –Centric learning Project Investigator:Prof. D V L N Somayajulu
Views: 6226 Vidya-mitra
Dealing With Noisy Data : Binning Technique [Data Mining] (HINDI)
 
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📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 18786 5 Minutes Engineering
Data Preprocessing Techniques using Rapid Minor
 
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Video contains - Import and Export data - Normalization - Sampling - Data Cleansing - Aggregation
Views: 530 Aditya Chandra
Weka Tutorial 03: Classification 101 using Explorer (Classification)
 
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In this tutorial, classification using Weka Explorer is demonstrated. This is the very basic tutorial where a simple classifier is applied on a dataset in a 10 Fold CV. For more variations of classification, watch out other tutorials on this channel.
Views: 161670 Rushdi Shams
Heuristic 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: 3349 Laurel Powell
Data Collection and Preprocessing | Lecture 6
 
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Deep Learning Crash Course playlist: https://www.youtube.com/playlist?list=PLWKotBjTDoLj3rXBL-nEIPRN9V3a9Cx07 Highlights: Garbage-in, Garbage-out Dataset Bias Data Collection Web Mining Subjective Studies Data Imputation Feature Scaling Data Imbalance #deeplearning #machinelearning
Views: 2207 Leo Isikdogan
Machine Learning Data preprocessing Feature Scaling In scikitLearn-1  Part-15
 
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Hi Guys checkout my udemy course at just 9.99$ https://www.udemy.com/data-science-with-python-and-pandas/?couponCode=KNOWLEDGE_IS_POWER https://www.udemy.com/manipulate-excel-file-from-python-openpyxl/?couponCode=KNOWLEDGE_IS_POWER https://www.udemy.com/learn-docker-from-scratch/?couponCode=KNOWLEDGE_IS_POWER https://www.udemy.com/learn-in-memory-database-redis-from-scratch/?couponCode=KNOWLEDGE_IS_POWER https://www.udemy.com/learn-event-processing-with-logstash-elk-stack/?couponCode=KNOWLEDGE_IS_POWER https://www.udemy.com/machine-learning-and-bigdata-analysis-with-apache-spark-python-pyspark/?couponCode=KNOWLEDGEISPOWER https://www.udemy.com/data-science-and-machine-learning-in-r-programming/?couponCode=KNOWLEDGE_IS_POWER This video will explain how to do feature scaling with scikit learn machine learning libray in python. MinMax Scalar: X_std = (X - X.min(axis=0)) / (X.max(axis=0) - X.min(axis=0)) X_scaled = X_std * (max - min) + min x = np.array([[1.,2,3],[4,5,6],[7,8,9]]) minmax = preprocessing.MinMaxScaler(feature_range=(0,1)) minmax.fit(x).transform(x) Standard Scalar : 0 Mean, Unit Variance Standard Scaler (x-mean)/xstd standard = preprocessing.StandardScaler().fit(x) standard.transform(x)
Views: 11927 MyStudy
L20: Data Integration and Transformation in data mining | data integration algorithms
 
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L20: Data Integration and Transformation in data mining | data integration algorithms Namaskar, In the Today's lecture, I will cover Data Transformation of subject Data Warehousing and Data Mining I am Sandeep Vishwakarma (www.universityacademy.in) from Raj Kumar Goel Institute of Technology Ghaziabad. I have started a YouTube Channel Namely “University Academy” Teaching Training and Informative. On This channel am providing following services. 1 . Teaching: Video Lecture of B.Tech./ M.Tech. Technical Subject who provide you deep knowledge of particular subject. Compiler Design: https://www.youtube.com/playlist?list=PL-JvKqQx2Ate5DWhppx-MUOtGNA4S3spT Principle of Programming Language: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdIkEFDrqsHyKWzb5PWniI1 Theory of Automata and Formal Language: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdhlS7j6jFoEnxmUEEsH9KH 2. Training: Video Playlist of Some software course like Android, Hadoop, Big Data, IoT, R programming, Python, C programming, Java etc. Android App Development: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdBj8aS-3WCVgfQ3LJFiqIr 3. Informative: On this Section we provide video on deep knowledge of upcoming technology, Innovation, tech news and other informative. Tech News: https://www.youtube.com/playlist?list=PL-JvKqQx2AtdFG5kMueyK5DZvGzG615ks Other: https://www.youtube.com/playlist?list=PL-JvKqQx2AtfQWfBddeH_zVp2fK4V5orf Download You Can Download All Video Lecture, Lecture Notes, Lab Manuals and Many More from my Website: http://www.universityacademy.in/ Regards University Academy UniversityAcademy Website: http://www.universityacademy.in/ YouTube: https://www.youtube.com/c/UniversityAcademy Facebook: https://www.facebook.com/UniversityAcademyOfficial Twitter https://twitter.com/UniAcadofficial Instagram https://www.instagram.com/universityacademyofficial Google+: https://plus.google.com/+UniversityAcademy
Views: 596 University Academy
Data Cleaning In Python (Practical Examples)
 
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Data Cleaning In Python with Pandas In this tutorial we will see some practical issues we have when working with data,how to diagnose them and how to solve them. ==Tutorial and Data Set here== Github: https://goo.gl/erg89C Blog: https://goo.gl/6PJsdo Reference ====Common Data Cleaning Issues==== Reading File Inconsistent Column Names Missing Data Duplicates Inconsistent Data Types Outliers Noisy Data etc.
Views: 16891 J-Secur1ty
Data preprocessing: Column standardization-Dimensionality reduction Lecture 7@ Applied AI Course
 
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for more information please visit https://www.appliedaicourse.com
Views: 2403 Applied AI Course
Weka Tutorial 01: ARFF 101 (Data Preprocessing)
 
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Weka Machine Learning Tutorial on how to prepare an arff file
Views: 205050 Rushdi Shams
weka j48 classification tutorial
 
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This is a tutorial for the Innovation and technology course in the ePC-UCB. La Paz Bolivia
Views: 56764 Alejandro Peña
Introduction to Data Mining: Data Aggregation
 
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In this Data Mining Fundamentals tutorial, we discuss our first data cleaning strategy, data aggregation. Aggregation is combining two or more attributes (or objects) into a single attribute (or object). -- Learn more about Data Science Dojo here: https://hubs.ly/H0hCnj10 Watch the latest video tutorials here: https://hubs.ly/H0hCnHV0 See what our past attendees are saying here: https://hubs.ly/H0hCnj40 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 830 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 11595 Data Science Dojo
NLP - Text Preprocessing and Text Classification (using Python)
 
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Hi! My name is Andre and this week, we will focus on text classification problem. Although, the methods that we will overview can be applied to text regression as well, but that will be easier to keep in mind text classification problem. And for the example of such problem, we can take sentiment analysis. That is the problem when you have a text of review as an input, and as an output, you have to produce the class of sentiment. For example, it could be two classes like positive and negative. It could be more fine grained like positive, somewhat positive, neutral, somewhat negative, and negative, and so forth. And the example of positive review is the following. "The hotel is really beautiful. Very nice and helpful service at the front desk." So we read that and we understand that is a positive review. As for the negative review, "We had problems to get the Wi-Fi working. The pool area was occupied with young party animals, so the area wasn't fun for us." So, it's easy for us to read this text and to understand whether it has positive or negative sentiment but for computer that is much more difficult. And we'll first start with text preprocessing. And the first thing we have to ask ourselves, is what is text? You can think of text as a sequence, and it can be a sequence of different things. It can be a sequence of characters, that is a very low level representation of text. You can think of it as a sequence of words or maybe more high level features like, phrases like, "I don't really like", that could be a phrase, or a named entity like, the history of museum or the museum of history. And, it could be like bigger chunks like sentences or paragraphs and so forth. Let's start with words and let's denote what word is. It seems natural to think of a text as a sequence of words and you can think of a word as a meaningful sequence of characters. So, it has some meaning and it is usually like,if we take English language for example,it is usually easy to find the boundaries of words because in English we can split upa sentence by spaces or punctuation and all that is left are words.Let's look at the example,Friends, Romans, Countrymen, lend me your ears;so it has commas,it has a semicolon and it has spaces.And if we split them those,then we will get words that are ready for further analysis like Friends,Romans, Countrymen, and so forth.It could be more difficult in German,because in German, there are compound words which are written without spaces at all.And, the longest word that is still in use is the following,you can see it on the slide and it actually stands forinsurance companies which provide legal protection.So for the analysis of this text,it could be beneficial to split that compound word intoseparate words because every one of them actually makes sense.They're just written in such form that they don't have spaces.The Japanese language is a different story.
Views: 9127 Machine Learning TV
More Data Mining with Weka (2.3: Discretization in J48)
 
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More Data Mining with Weka: online course from the University of Waikato Class 2 - Lesson 3: Discretization in J48 http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/QldvyV https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 9799 WekaMOOC
2. Learning Data Preprocessing with Pima Indians Diabetes data
 
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Logistic regression is used when the response variable is categorical in nature. For instance, yes/no, true/false, red/green/blue, 1st/2nd/3rd/4th, etc. As opposed to this, Linear regression is used when your response variable is continuous. For instance, weight, height, number of hours, etc. Logistic Regression proves to be of great use mainly in two scenarios: 1. "As is": The probability output of the regression can be treated as a discrete output. 2. "Binary Output": A threshold value can be applied to the probabilistic output of the regression model and a value '1' can be assigned to the model's output if the predicted value is greater than this threshold. In other words, y'= 1 if predicted(x) is greater than 0.5 where 0.5 is our threshold. The second approach is how logistic regression is used for classification. Have a look at this video from Google's Machine Learning Crash Course: https://youtu.be/uKSOY0yOHEQ Pima Indians Diabetes dataset: https://www.kaggle.com/wanglaiqi/pimaindiansdiabetesdata
Views: 659 MLCC_PICT Pune