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

• https://botlnec.github.io/islp/
• https://github.com/a-martyn/ISL-python
• https://github.com/mscaudill/IntroStatLearn