AI News, In-depth introduction to machine learning in 15 hours of expert videos
In-depth introduction to machine learning in 15 hours of expert videos
In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an online course based on their newest textbook, An Introduction to Statistical Learning with Applications in R (ISLR).
(Update: The course will be offered again in January 2016!) If you are new to machine learning (and even if you are not an R user), I highly recommend reading ISLR from cover-to-cover to gain both a theoretical and practical understanding of many important methods for regression and classification.
Never miss an update! Subscribe to R-bloggers to receive e-mails with the latest R posts. (You will not see this message again.)
I found it to be an excellent course in statistical learning (also known as “machine learning”), largely due to the high quality of both the textbook and the video lectures.
If you are new to machine learning (and even if you are not an R user), I highly recommend reading ISLR from cover-to-cover to gain both a theoretical and practical understanding of many important methods for regression and classification.
R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...
This 30 page guide will show you how to install R, load data, run analyses, make graphs, and more.
Swirl provides exercises and feedback from within your R session to help you learn in a structured, interactive way.
These free events teach you how do do useful things in R, and we’re always making more. Our previous webinars are archived into several tracks for your viewing convenience: Tip: Look at our two-part series on “Working with the RStudio IDE” at DataCamp to master all features of the IDE.
This book will teach you how to use the most modern parts of R to import, tidy, transform, visualize, and model data, as well as how to communicate findings with R Markdown.
You can search for R packages and functions, look at package download statistics, and leave and read comments about R functions.
If you need a quick reminder about how to wrangle data, make a graph, or do some other common task in R download one of our free R cheat sheets.
Or, take Hadley’s online course “Writing Functions in R” where he teaches you the fundamentals of writing functions in R so you can make your code more readable, avoid coding errors, and automate repetitive tasks.
- On Tuesday, June 25, 2019
1. Introduction to Statistics
NOTE: This video was recorded in Fall 2017. The rest of the lectures were recorded in Fall 2016, but video of Lecture 1 was not available. MIT 18.650 Statistics for Applications, Fall 2016...
Discovering Statistics Using R
Video made at the request of my publishers to promote my new textbook (out March 2012) 'Discovering Statistics Using R'. Despite what I say in this video, the book ended up being printed in...
Statistics with R: Introduction to Data Types, Lesson 1 by Courtney Brown
Lesson 1: Introduction to Data Types. This lecture was given at Emory University in Atlanta, Georgia on 1 September 2013. In this lesson, data types are discussed, as well as methods for collecting...
Statistics with R: Logistic Regression, Lesson 19 by Courtney Brown
Lesson 19: Logistic Regression. This lecture was given at Emory University in Atlanta, Georgia on 3 December 2013. Logistic regression is discussed as an approach to multiple regression when...
Modern Data Science with R: Overview of "Supervised learning"
Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather...
Statistics with R: Using R and RStudio, Lesson 2 by Courtney Brown
Lesson 2: Using R and RStudio. This lecture was given at Emory University in Atlanta, Georgia on 5 September 2013. Lesson 2 describes how to begin using the R Programming Language and RStudio...
R tutorial: Introduction to cleaning data with R
Learn more about cleaning data with R: Hi, I'm Nick. I'm a data scientist at DataCamp and I'll be your instructor for this course on Cleaning..
Statistics with R: Regression, Lesson 9 by Courtney Brown
Lesson 9 : Introduction to Regression. This lecture was given at Emory University in Atlanta, Georgia on 17 October 2013. Bivariate regression is explained. Statistics and concepts addressed...