Students are rushing to master powerful machine learning techniques for improving decision-making and scaling analysis to immense datasets. Machine Learning with Python for Everyone brings together all they'll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently. Reflecting 20 years of experience teaching non-specialists, the author teaches through carefully-crafted datasets that are complex enough to be interesting, but simple enough for non-specialists. Building on this foundation, the book presents real-world case studies that apply his lessons in detailed, nuanced ways. Throughout, he offers clear narratives, practical &ldquocode-alongs," and easy-to-understand images focusing on mathematics only where it's necessary to make connections and deepen insight." Table of Content Chapter
1: Let's Discuss Learning Chapter
2: Predicting Categories: Getting Started with Classification Chapter
3: Predicting Numerical Values: Getting Started with Regression Chapter
4: Evaluating and Comparing Learners Chapter
5: Evaluating Classifiers Chapter
6: Evaluating Regressors Chapter
7: More Classification Methods Chapter
8: More Regression Methods Chapter
9: Manual Feature Engineering: Manipulating Data for Fun and Profit Chapter
10: Models That Engineer Features for Us Chapter
11: Feature Engineering for Domains: Domain-Specific Learning Online Chapters Chapter
12: Tuning Hyperparameters and Pipelines Chapter
13: Combining Learners Chapter
14: Connections, Extensions, and Further Directions Salient Features
1. Covers whatever learners need to succeed in data science with Python: process, code, and implementation
2. Enables learners to understand the machine learning process, leverage the powerful Python scikit-learn library, and master the algorithmic components of learning systems
3. Integrates clear narrative, carefully designed Python code, images, and interesting, intelligible datasets