Data Science Projects with Python: A case study approach to gaining valuable insights from real data with machine learning, 2nd Edition

This book is a comprehensive guide to machine learning with Python, providing hands-on experience with industry-standard techniques and tools.

With real-world examples and practical exercises, you'll learn how to load, explore, and process data using pandas, Matplotlib, and scikit-learn, before moving on to fitting, evaluating, and tuning algorithms such as regularized logistic regression and random forest.

The book also covers brand new content on XGBoost, SHAP values, algorithmic fairness, and the ethical concerns of deploying a model in the real world.

By the end of this data science book, you'll have the skills, understanding, and confidence to build your own machine learning models and gain insights from real data.

Get started today and unlock the power of machine learning with Python!