This repository is created as complementary to our Machine Learning Book Cracking The Machine Learning Interview. Our book is available worldwide on Amazon.

Brief description of our book:

1. It equips you with 225 of the best Machine Learning problems along with their solutions.
2. It requires only a basic knowledge of fundamental mathematical and statistical concepts.
3. It assists in learning the intricacies underlying Machine Learning concepts and algorithms suited to specific problems.
4. It uniquely provides a manifold understanding of both statistical foundations and applied programming models for solving problems.
5. It discusses key points and concrete tips for approaching real life system design problems and imparts the ability to apply them to your day to day work.
6. It can be used by students and professionals alike. It has been drafted in a way to benefit both, novices as well as individuals with substantial experience in Machine Learning.

In this repository, we share code snippets for the solutions discussed in our book to demonstrate their usage.

Language used : Python

Framework used: Scikit-Learn

Do check out our book and share your feedback. You can email us at [email protected].

The repository is structured as follows:

• General Machine Learning Questions
• Natural Language Processing
• Supervised Learning
  • Classification
    • Artificial Neural Networks
    • Decision Trees
    • K-Nearest Neighbors
    • Logistic Regression
    • Support Vector Machines
  • Regression
• Unsupervised Learning
  • Clustering