This tutorial is a set of 15 hour videos by acclaimed experts in the area of machine learning and statistics from Stanford. It is suitable for Beginners as well as experts

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).

As a supplement to the textbook, you may also want to watch the excellent course lecture videos (linked below), in which Dr. Hastie and Dr. Tibshirani discuss much of the material. In case you want to browse the lecture content, I’ve also linked to the PDF slides used in the videos. For basics of Machine Learning please read through – Introduction to Machine Learning

I will highly recommend you to bookmark this page and use it as a reference whenever required.

Chapter 1: Introduction (slides, playlist)

Chapter 2: Statistical Learning (slides, playlist)

Chapter 3: Linear Regression (slides, playlist)

Other Preparatory Regression Tutorials

Chapter 4: Classification (slides, playlist)

Chapter 5: Resampling Methods (slides, playlist)

Chapter 6: Linear Model Selection and Regularization (slides, playlist)

Chapter 7: Moving Beyond Linearity (slides, playlist)

Chapter 8: Tree-Based Methods (slides, playlist)

Chapter 9: Support Vector Machines (slides, playlist)

Chapter 10: Unsupervised Learning (slides, playlist)

Interviews (playlist)


The article was originally posted at Here.

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One thought on “Tutorial : Beginner to advanced machine learning in 15 hour Videos

  1. Hi Shantanu ,

    You are absolutely a great and organised person.You have made life so simple by sharing all the videos and presentations from the one the best professors in the world.

    I have started learning all these from here. Your website is too good and probably the most organised websites to learn data sciences.

    Like

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