ler totalmente Machine Learning Basics with Python - Level 3 (Data Analysis with Python) (English Edition)

Machine Learning Basics with Python

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 Google Colab notebooks included — start instantly in your browser, no setup required.

• Chapter-linked notebooks for hands-on practice
• Python syntax reference notebook
• Beginner-friendly code, explained step by step

This book uses a fixed layout. Please use it on a large screen such as a PC or tablet.

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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