Book Contents Part I: Understanding Machine Learning Chapter 1: Machine Learning Basics details Chapter 2: The Python Machine Learning Ecosystem details Part II: The Machine Learning Pipeline Chapter 3: Processing, Wrangling and Visualizing Data details Chapter 4: Feature Engineering and Selection details Chapter 5: Building, Tuning and Deploying Models details Part III: Real-World Case Studies Chapter 6: Analyzing Bike Sharing Trends details Chapter 7: Analyzing Movie Reviews Sentiment details Chapter 8: Customer Segmentation and Effective Cross Selling details Chapter 9: Analyzing Wine Types and Quality details Chapter 10: Analyzing Music Trends and Recommendations details Chapter 11: Forecasting Stock and Commodity Prices details Chapter 12: Deep Learning for Computer Vision details
