This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning
An-Introduction-to-Statistical-Learning is one of the most popular books among data scientists to learn the conepts and intuitions behind machine learning algorithms, however, the exercises are implemented in R language, which is a hinderence for all those who are using python language. To overcome this i have tried solving all the questions in practical exerices in Python language, so people using python language can also get the most our of this amazing book. Along with that i have also provided the solutions for conceptual questions. I had tried my best to write the correct solutions to the problem, It was a challenge, and i need to learn to do a lot of research. I do not gurantee that all the solutions are absoletely correct. I have commented the notebooks. If you find any query, do send a feedback about the same. Suggestions and corrections are welcome. this is my email - [email protected] Happy Learning!
- Chapter_2_Statistical_Learning
- Chapter_3_Linear_Regression
- Chapter_4_Classification
- Chapter_5_Resampling_Methods
- Chapter_6_Linear_Model_Selection_and_Regularization
- Chapter_7_Moving_Beyond_Linearity
- Chapter_8_Tree_Based_Methods
- Chapter_9_Support_Vector_Machines
- Chapter_10_Unsupervised_Learning
REFERENCES