Level 3: Scikit-Learn Foundations:
From Regression & Classification to Decision Trees,
Clustering & Model Evaluation….
Math & Python Textbook Series 7
“Curiosity about mathematics,
the foundation of everything in the AI era.”
Two free downloadable files : Hands-On Data Analysis with Python
Efficient learning with Colab note files linked to this book.
Beginner-friendly Python code explained step-by-step.
FilesStart Instantly in Your Browser—No Setup!
Contents
Chapter 1 What Is Machine Learning and Data Science?
Chapter 2 Getting Python Ready for Machine Learning
Chapter 3 The Basic Flow of Machine Learning
Chapter 4 Getting Data Ready for Machine Learning
Chapter 5 Creating Features
Chapter 6 Regression: Predicting Numbers
Chapter 7 Classification: Predicting Categories or Outcomes
Chapter 8 Decision Trees: Predicting with Branching Conditions
Chapter 9 Random Forests: Predicting with Many Trees
Chapter 10 Evaluating a Model: What Makes a Good Prediction?
Chapter 11 Evaluating Classification Models in Detail
Chapter 12 Clustering: Grouping Similar Data
Chapter 13 Dimensionality Reduction: Making Data Easier to See
Chapter 14 Time Series Data and Prediction
Chapter 15 Analyzing Text Data
Chapter 16 The Basics of AI and Generative AI
Chapter 17 Practical Project: Building a Prediction Model from Data
Appendix A scikit-learn Mini-Dictionary
Appendix B Evaluation Metrics for Machine Learning
Appendix C Common Preprocessing Steps
Appendix D A Data Science Project Template
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