An Introduction To Statistical Learning with Applications In R [Free Book Version With Videos]
Hi. I have been reviewing some statistics along with learning machine learning as of late. The book I am using is called An Introduction To Statistical Learning with Applications In R.
This book also has corresponding educational videos for visual type learners. Even though the authors call it statistical learning, the concepts in the book/videos are found in machine learning tutorials. (Different gift wrapping, same stuff inside.)
I have found about these videos through Google searching and finding this post from R-Bloggers here. The Youtube videos need to be accessed through links. They are not searchable publicly.
This book (video series) contains a good mix of theory and practice in learning machine learning. Programming sections in the videos are done in R. If you are using Python, you may want to refer to videos by someone like sentdex for the programming portion.
Main Topics
- Linear Regression & Its Variants
- Model Selection & Model Diagnostics
- Classification (K-Nearest Neighbours, Logistic Regression)
- Resampling Methods (Cross-Validation, Bootstrapping)
- Polynomial Regression (Cubic Splines)
- Tree Based Methods
- Unsupervised Learning
- Support Vector Machines
After going through bits and pieces of the videos, I would say that it is helpful to have knowledge in (multivariable) calculus, linear algebra, and basic statistics. The level of the topics (in my opinion) are at the upper undergraduate level with a few topics such as LASSO at the graduate level.
What This Does Not Cover
- Time Series Analysis (Advanced Econometrics For Economics People)
- Survival Analysis
- Neural Networks
- Monte Carlo Methods
- Text Mining
Other resources and videos would be needed for the list above.
I think this book and the supplementary videos are good for applied statistics people and to those who want a good introduction to machine learning. There is a bit of math in this but I think it helps with understanding before doing.
Following R Bloggers has taught me so much. Thanks for sharing resources!
Datacamp is a good resource as well. I used their website when they had student pricing. Their cheatsheets are really good.
That's a great book for learning ML.
The authors for the book are great too.