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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 Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. 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: 49565 edureka!
Rattle - Data Mining in R
 
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Overview of using Rattle - a GUI data mining tool in R. Overview covers some of the basic operations that can be performed in Rattle such as loading data, exploring the data and applying some of the data mining algorithms on the data - all this without actually having to type any R code
Views: 34478 Melvin L
Downloading Data from Google Trends And Analyzing It With R
 
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Follow me on Twitter @amunategui Check out my new book "Monetizing Machine Learning": https://amzn.to/2CRUOKu In this video, I introduce Google Trends by querying it directly through the web, downloading a comma-delimited file of the results, and analyzing it in R. Full walkthrough and code: http://amunategui.github.io/google-trends-walkthrough/ Support these videos, check out my in-depth classes on Udemy.com (discounts and specials) at http://amunategui.github.io/udemy/
Views: 20409 Manuel Amunategui
R - Twitter Mining with R (part 1)
 
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Twitter Mining with R part 1 takes you through setting up a connection with Twitter. This requires a couple packages you will need to install, and creating a Twitter application, which needs to be authorized in R before you can access tweets. We quickly go through this entire process which may take some flexibility on your part so be patient and be ready troubleshoot as details change with updates. Warning: You are going to face challenges setting up the twitter API connection. The steps for this part have been known to change slightly over time for a variety of reasons. Follow the general steps and expect a few errors along the way which you will have to troubleshoot. It is hard to solve these issues remotely from where I am.
Views: 62938 Jalayer Academy
Data Mining Tool:Rattle R GUI
 
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Link to download R Console: https://cran.r-project.org/
Views: 2945 Chandrakala Badaga
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: 855006 David Langer
Download R and RStudio
 
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Download R and RStudio
Views: 7233 DWR447
Google Analytics Data Mining with R (includes 3 Real Applications)
 
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R is already a Swiss army knife for data analysis largely due its 6000 libraries but until now it lacked an interface to the Google Analytics API. The release of RGoogleAnalytics library solves this problem. What this means is that digital analysts can now fully use the analytical capabilities of R to fully explore their Google Analytics Data. In this webinar, Andy Granowitz, ‎Developer Advocate (Google Analytics) & Kushan Shah, Contributor & maintainer of RGoogleAnalytics Library will show you how to use R for Google Analytics data mining & generate some great insights. Useful Resources:http://bit.ly/r-googleanalytics-resources
Views: 28187 Tatvic Analytics
R Programming Import Data from URL
 
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Learn how to Import Data from URL in R Programming Language.
Views: 7443 DevNami
How to Install Packages in R (R Tutorial 1.12)
 
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Learn how to find and install packages for R, using the "install.packages" command or menu options in RStudio. This video is a tutorial for programming in R Statistical Software for beginners. Here is an overview of the topics discussed in this video. You can click on the time stamp to jump to the specific topic. 0:00:12 what are packages in R and why use them 0:00:46 how to access help menu for packages in R when using the "install.packages" command 0:01:00 how to install packages in R using "install.packages" command when you know the name of the package 0:01:53 how to install packages in R using "install.packages" command when you don't know the name of the package 0:02:48 how to load the library of commands and functions for a package in R 0:03:17 how to access and download packages for R from 'R-project.org' website 0:04:30 how to access help menu for a specific package in R 0:04:57 how to remove a package from R using "remove.packages" command 0:05:11 how to install packages in R using the menus in RStudio
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: 21889 Hong Qin
R and data mining
 
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Short demo for using R in data mining.
Views: 166 Li Wang
Text Analytics With R | How to Connect Facebook with R | Analyzing Facebook in R
 
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In this text analytics with R tutorial, I have talked about how you can connect Facebook with R and then analyze the data related to your facebook account in R or analyze facebook page data in R. Facebook has millions of pages and getting emotions and text from these pages in R can help you understand the mood of people as a marketer. Text analytics with R,how to connect facebook with R,analyzing facebook in R,analyzing facebook with R,facebook text analytics in R,R facebook,facebook data in R,how to connect R with Facebook pages,facebook pages in R,facebook analytics in R,creating facebook dataset in R,process to connect facebook with R,facebook text mining in R,R connection with facebook,r tutorial for facebook connection,r tutorial for beginners,learn R online,R beginner tutorials,Rprg
Rattle for Data Mining - Using R without programming (CRAN)
 
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www.learnanalytics.in demostrates use of an free and open source platform to build sophisticated predictive models. We demonstrate using R package Rattle to do data analysis without writing a line of r code. We cover hypothesis testing, descriptive statistics, linear and logistic regression with a flavor of machine learning (Random Forest, SVM etc.). Also using graphs such as ROC curves and Area under curves (AUC) to compare various models. To download the dataset and follow on your own follow http://www.learnanalytics.in/datasets/Credit_Scoring.zip
Views: 41807 Learn Analytics
Get Twitter Data into R
 
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Tutorial on how to download twitter data into R. Link to code below. Brackets aren't allowed in YouTube descriptions (which means I can't include the R code in here, link to code - http://storybydata.com/get-twitter-data-into-r-tutorial/
Views: 3086 Story by Data
Datamining project using R progamming part1
 
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code in R programming and ppt . Project:Stock predictor for pharmacy(Tablets). Data mining in R Studio
Views: 9766 Saiprasad Shettar
R Programming, Data Mining
 
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R Programming, Data Mining
Views: 496 ScholarsPro
R - Install R packages from CRAN
 
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General discussion on R packages from CRAN, how to install them, and how to load them in an R session.
Views: 15992 Jalayer Academy
R Tutorial #1 - Download, Installation, Setup - Statistical Programming Language R
 
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Part 1 of my R Tutorial - Download, installation and setup. R is a programming language and software environment for statistical computing and graphics. The R language has become a de facto standard among statisticians for the development of statistical software, and is widely used for statistical software development and data analysis. R is part of the GNU project. The website for R is http://www.r-project.org/ Also the Wikipedia article for R is useful to get a first impression of R.
Views: 125708 Tutorlol
Apriori Algorithm with R Studio
 
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This is a video for RMD Sinhgad School of Engineering (BE-Computer) as a demonstration for one of the assignments of Business Analytics and Intelligence. Important Links: Ubuntu 16.04.2 LTS Download: https://www.ubuntu.com/download/desktop R installation instructions: https://www.datascienceriot.com/how-to-install-r-in-linux-ubuntu-16-04-xenial-xerus/kris/ R studio Download: https://www.rstudio.com/products/rstudio/download/ R Tutorial: http://tryr.codeschool.com/
Views: 5883 Varun Joshi
Install RStudio on Windows - Data Analysis with R
 
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This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 18921 Udacity
R Tutorial 01  Installing R
 
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R Tutorial 01: Installing R This lesson shows you how to get started with R by installing the software in a windows pc / computer. R is a programming language for statistical computing. Download and Install your R console. This video demonstrates a customized setup so as to enable easy maneuver while coding. Visit www.rstatistics.net for written R tutorials and more. The software that is used for data mining / machine learning / data science / statistical computing and mathematical problem solving.
Views: 64 Gladwin Analytics
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: 10396 Bharatendra Rai
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 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/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: 46523 Data Science Dojo
Downloading and Installing R and RStudio on Mac or Windows
 
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Provides steps for downloading and installing R and RStudio on Mac or Windows. Playlist: https://www.youtube.com/playlist?list=PL34t5iLfZddv8tJkZboegN6tmyh2-zr_T 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: 4310 Bharatendra Rai
Scraping Web Data in R - Rvest Tutorial
 
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A short video tutorial for downloading website data into R using the Rvest package. I have used it countless times in my own RStats web scraping projects, and I have found it to be especially useful for R webscraping projects that involve a static HTML webpage. This guide will also cover installing/using the Selector Gadget tool. The Rvest package is available on CRAN. Visit http://www.selectorgadget.com for more information on Selector Gadget. In this video, we will download web data using RStudio and Google Chrome.
Views: 10830 R You Ready For It?
R Tutorial - 5 - Know About R Studio Interface For Beginners [5/13]
 
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R Tutorial - 5 - Know About R Studio Interface For Beginners [5/13] Official Link :- https://cran.r-project.org/ https://www.r-project.org/ Download R Studio:- https://www.rstudio.com/products/rstudio/download/ In this video , We will learn about R Studio Interface. After this video, you will understand and start to work with R Studio in more effective way. What is R ? R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. Currently top most world wide compniese hiring for R developers. According to Data Science survay 2015,2016 R developer demands are very high. Subscribe to our YouTube channel at https://www.youtube.com/channel/UC6U2o83YHhhtM9W7IzWAPRA Also please like my facebook page :- https://www.facebook.com/learnetix/?ref=bookmarks Please comment down if you getting any issue regarding technical contain and also please share with others. Keywords :- r (programming language), r tutorial, introduction to r, data science, getting started with r, software tutorial, learning r, data analysis, statistical data analysis, machine learning (software genre), learn r, reading data into r, data mining (software genre), r-software, r analytics tutorial, r analytics training, r analytics, r predictive analytics, r analysis tutorial, data analysis (media genre), data scientist, data scientist tutorial -~-~~-~~~-~~-~- Please watch: "Apache Pig Tutorial | 1. Introduction to Apache Pig | Hadoop Pig Tutorial For Beginners" https://www.youtube.com/watch?v=RXAuNhho5do -~-~~-~~~-~~-~-
Views: 217 Nandan Priyadarshi
Hands-on dplyr tutorial for faster data manipulation in R
 
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dplyr is a new R package for data manipulation. Using a series of examples on a dataset you can download, this tutorial covers the five basic dplyr "verbs" as well as a dozen other dplyr functions. Watch the follow-up tutorial: http://youtu.be/2mh1PqfsXVI View the R Markdown document: http://rpubs.com/justmarkham/dplyr-tutorial Download the source document: https://github.com/justmarkham/dplyr-tutorial Read about why I love dplyr: https://www.dataschool.io/dplyr-tutorial-for-faster-data-manipulation-in-r/ Tutorial contents: 1. Introduction to dplyr (starts at 0:00) 2. Loading dplyr and the example dataset (starts at 2:29) 3. Understanding "local data frames" (starts at 3:23) 4. Verb #1: `filter` (starts at 5:17) 5. Verb #2: `select`, plus `contains`, `starts_with`, `ends_with`, `matches` (starts at 7:54) 6. Using chaining syntax for more readable code (starts at 9:34) 7. Verb #3: `arrange` (starts at 12:53) 8. Verb #4: `mutate` (starts at 13:55) 9. Verb #5: `summarise`, plus `group_by`, `summarise_each`, `n`, `n_distinct`, `tally` (starts at 15:31) 10. Window functions: `min_rank`, `top_n`, `lag` (starts at 26:47) 11. Convenience functions: `sample_n`, `sample_frac`, `glimpse` (starts at 32:44) 12. Connecting to databases (starts at 34:21) == RESOURCES == Reference manual and vignettes: http://cran.r-project.org/web/packages/dplyr/index.html July 2014 webinar: http://pages.rstudio.net/Webinar-Series-Recording-Essential-Tools-for-R.html July 2014 webinar code: https://github.com/rstudio/webinars/tree/master/2014-01 Tutorial by Hadley Wickham: https://www.dropbox.com/sh/i8qnluwmuieicxc/AAAgt9tIKoIm7WZKIyK25lh6a GitHub repo: https://github.com/hadley/dplyr List of releases: https://github.com/hadley/dplyr/releases == 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: 147290 Data School
Web Data Mining com R
 
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Web Data Mining com R
Views: 1430 Antonio Correa
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; 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. ▶︎How to import CSV data into R? We will be using "read.table" command to import comma separated data into R ▶︎ How to import txt data file into R? You will learn to use "read.delim" command 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: ▶︎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? "read.csv" command 0:01:44 How to access the help menu for different commands in R 0:02:04 How to specify file location in R? "file.choose" argument on "read.csv" command 0:02:31 How to let R know data has headers or variable names: the "header" argument on "read.csv" command to 0:03:22 How to import CSV file into R? "read.table" command 0:03:38 How to specify the file location in R for "read.table" command? "file.choose" argument 0:03:46 How to let R know how the data values are separated? the "sep" argument on "read.table" command 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? "read.delim" command 0:05:44 How to to specify the file path in R for "read.delim" command? "file.choose" argument 0:06:06 How to import tab-delimited (.txt) data file into R? "read.table" command 0:06:23 How to let R know that the data has headers or variable? "header" argument on "read.table" command 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: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
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: 191401 David Sherlock
R Tutorial - 6 - Variable and Constant in R For Beginners [6/13]
 
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R Tutorial - 6 - Variable and Constant in R For Beginners [6/13] Official Link :- https://cran.r-project.org/ https://www.r-project.org/ Download R Studio:- https://www.rstudio.com/products/rstudio/download/ In this video , We will learn about R Studio Interface. After this video, you will understand about variable and constant in R with example. What is R ? R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. Currently top most world wide compniese hiring for R developers. According to Data Science survay 2015,2016 R developer demands are very high. Subscribe to our YouTube channel at https://www.youtube.com/channel/UC6U2o83YHhhtM9W7IzWAPRA Also please like my facebook page :- https://www.facebook.com/learnetix/?ref=bookmarks Please comment down if you getting any issue regarding technical contain and also please share with others. Keywords :- r (programming language), r tutorial, introduction to r, data science, getting started with r, software tutorial, learning r, data analysis, statistical data analysis, machine learning (software genre), learn r, reading data into r, data mining (software genre), r-software, r analytics tutorial, r analytics training, r analytics, r predictive analytics, r analysis tutorial, data analysis (media genre), data scientist, data scientist tutorial -~-~~-~~~-~~-~- Please watch: "Apache Pig Tutorial | 1. Introduction to Apache Pig | Hadoop Pig Tutorial For Beginners" https://www.youtube.com/watch?v=RXAuNhho5do -~-~~-~~~-~~-~-
Views: 178 Nandan Priyadarshi
Introduction to R: Data Exploration & Alteration
 
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Here we introduce the built-in functions for data exploration and alteration. Download R: https://cran.r-project.org/ Download RStudio: https://www.rstudio.com/products/rstu... -- At Data Science Dojo, we're extremely passionate about data science. 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/H0f8KcT0 See what our past attendees are saying here: https://hubs.ly/H0f8Kdg0 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://plus.google.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: 1959 Data Science Dojo
▶ How to Install Anaconda || Data Mining Tools Installation || Data Mining Software Setup
 
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Download, Install Anaconda, Jupyter Notebook, Spyder for Python Direct Download Link : https://www.anaconda.com/download/ »See Full #Data_Mining Video Series Here: https://www.youtube.com/watch?v=t8lSMGW5eT0&list=PL9qn9k4eqGKRRn1uBmEhlmEd58ATOziA1 In This Video You are gonna learn Data Mining #Bangla_Tutorial Data mining is an important process to discover knowledge about your customer behavior towards your business offerings. » My #Linkedin_Profile: https://www.linkedin.com/in/rafayet13 » Read My Full Article on Data Mining Career Opportunity & So On » Link: https://medium.com/@rafayet13 #Learn_Data_Mining_In_A_Easy_Way #Data_Mining_Essential_Course #Data_Mining_Course_For_Beginner ✔ How to Install Data Mining Tools || Anaconda Installation for Data Mining || Data Mining Software Install anaconda Distribution Package for data mining, data science, data analysis how to install anaconda python on windows how to install anaconda python on windows 10 Why You Should Use Anaconda for Python Development Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough ipython notebook
Views: 2098 BookBd
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: 428332 Brandon Weinberg
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: 25634 Bharatendra Rai
Twitter Data Mining using Python
 
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For complete professional training visit at: http://www.bisptrainings.com/course/Python-for-Beginners Follow us on Facebook: https://www.facebook.com/bisptrainings/ Follow us on Twitter: https://twitter.com/bisptrainings Email: [email protected] Call us: +91 975-275-3753 or +1 386-279-6856
Views: 27117 Amit Sharma
R Spatial Data 1: Read in SHP File
 
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Here we use R and RStudio to read in a spatial data file (as a SHP file), read in a contiguity (GAL) file created in GeoDa, create the same queen contiguity matrix in R and check that the two are the same, and compute a Moran's I. Link to Data File: https://sites.google.com/a/burkeyacademy.com/spatial/home/files/R%20Spatial%201%20Data.zip Link to Playlist of all Spatial Videos: https://www.youtube.com/playlist?list=PLlnEW8MeJ4z6Du_cbY6o08KsU6hNDkt4k My Website: http://www.burkeyacademy.com/ Support me on Patreon! https://www.patreon.com/burkeyacademy Talk to me on my SubReddit: https://www.reddit.com/r/BurkeyAcademy/ Link to download R: https://cloud.r-project.org/ Link to Download RStudio: https://www.rstudio.com/products/rstudio/download/ Here are the commands we used: library(spdep) library(rgdal) NCVACO = readOGR(dsn = ".", layer = "NCVACO") queen.nb=read.gal("queen.gal", region.id=NCVACO$FIPS) summary(queen.nb) queen.R.nb=poly2nb(NCVACO, row.names=NCVACO$FIPS) #Rook would be rook.R.nb=poly2nb(NCVACO,queen=FALSE) summary(queen.R.nb) isTRUE(all.equal(queen.nb,queen.R.nb,check.attributes=FALSE)) #moran(variable, listw, no. regions, sum of weights) moran(NCVACO$SALESPC,nb2listw(queen.nb), length(NCVACO$SALESPC), Szero(nb2listw(queen.nb))) moran.test(NCVACO$SALESPC,nb2listw(queen.nb))
Views: 5163 BurkeyAcademy
Sample Data in R | Sample datasets for data mining | sample data sets for statistical analysis
 
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Sample or in built datasets in R for beginners to quickly learn the tools without worrying much about real time data. In this video I've one through the some of the sample datasets available in R and how you can use it. Sample Data in R | Sample datasets for data mining | sample data sets for statistical analysis
Windows Tutorial on downloading and installing R and RStudio
 
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Download Links - R-project: http://cran.r-project.org/bin/windows/base/ RStudio: http://www.rstudio.com/ide/download/desktop
Views: 2450 TheCoatlessProfessor
IS 640 R Data Mining Project Solutions
 
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SOLUTION LINK: http://libraay.com/downloads/is-640-r-data-mining-project-solutions/ Use Random Forests, Neural Networks and Support Vector Machines to predict loan status (default or not). Understand the difference between in-sample fitting and out-of-sample predictive performance. Use two cross-validation methods to assess analytic model performance. Save this file on your desktop as yourlastname_640DM.docx. Load the Loan.csv data set into R. It lists the outcome of 850 loans. The data variables include loan status, credit grade (from excellent to poor), loan amount, loan age (in months), borrower’s interest rate and the debt to income ratio. Code loan status as a binary outcome (0 for current loans, 1 for late or default loans). Display the column names from the loan data set. Fit the loan data set using random forest function. Copy the trained random forest model and the confusion matrix from R and paste it below. [10 points] Randomly select 750 out of 850 loans as your training sample. Use the remaining 100 loans as your test set. Train the 2nd random forest model using the training set. Apply the 2nd model to the test set to predict loan status. Compare your predictions to the true loan statuses (using table function). Display the confusion matrix below. Based on this confusion matrix, what’s the overall misclassification rate? [10 points] Fit the loan data set using an artificial neural network. Use six neurons in the hidden layer of the ANN. Set maxit to 1000. Use table function to compare in-sample predictions to the true loan statuses. Display the confusion matrix below. [10 points]. Use the training sample (750 randomly selected loans) to build the 2nd artificial neural network. Use six neurons in the hidden layer of the ANN. Set maxit to 1000. Use table function to compare out-of-sample predictions to the true loan statuses (use the remaining 100 loans as your test set). Display the confusion matrix below. [10 points]. Use the training sample (750 randomly selected loans) to build a model of support vector machine. Use table function to compare the SVM’s out-of-sample predictions to the true loan statuses (use the remaining 100 loans as your test set). Display the confusion matrix below. [10 points]. Randomly shuffle the loan data set. Run 10-fold cross-validation to evaluate the out-of-sample performance of Random Forest, ANN and SVM. Based on your cross-validation results, which model has the best out-of-sample performance? Please briefly explain why. [30 points] Run leave-one-out cross-validation to evaluate the performance of random forest algorithm in predicting loan status. Why does it take much longer to run leave-one-out cross-validation than to run ten-fold cross-validation? Based on the result of your leave-one-out cross-validation, how many loans are misclassified by the random forest model?[20 points] Please save your word file as a pdf file named yourlastname_640DM.pdf. Submit the pdf file through the drop box in your Canvas account.
Views: 94 Libraay Downloads
Social Network Mining
 
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Social Network Mining Using R tool. termDocMatrix.rdata link:http://www.rdatamining.com/data If you are not able to install package using r tool then you can directly download the r package from below link. R data mining packages link:http://cran.r-project.org/web/packages/available_packages_by_name.html From this site download the .zip file of the package and after downloading the package open R tool and click on "packages" and select "install packages from local zip file". After successful installation you need to load the package.For loading the package click on "packages" and select "load packages" and then select the package you want to load. Get Great Deals on Amazon: https://goo.gl/jgZR7W Get Great Deals on Flipkart : https://goo.gl/MwgBfS Get Great Deals on Paytm : https://goo.gl/1XBQHr
Views: 5731 LetsGetGyan

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