Preface Part Ⅰ．The Fundamentals of Machine Learning 1．TheMachine Learning Landscape What Is Machine Learning Whr Use Machine Learning Examples of Applications Types of Machine Learning Systems Training Supervision Batch Versus Online Learning Instance Based Versus Model Based Learning Main Challenges of Machine Learning Insufficient Quantity of Training Data NonrepresentatiVe Training Data Poor-Quality Data Irrelevant Features Overfitting the Training Data Underfitting the Training Data Stepping Back Testing and Validating Hyperparameter Tuning and Model Selection Data Mismatch Exercises 2．End-to-End Machine Learning Project Working with Real Data Look at the Big Picture Frame the Problem Select a Performance Measure Check the Assumptions Get the Data Running the Code Examples Using Google Colab Saving Your Code Changes and Your Data The Power and Danger of Interactivity Book Code Versus Notebook Code Download the Data Take a Quick Look at the Data Structure Create a 11est Set Explore and Visualize the Data to Gain Insights Visualizing Geographical Data Look for Correlations Experiment with Attribute Combinations Prepare the Data for Machine Learning Algorithms Clean the Data Handling Text and Categorical Attributes Feature Scaling and Transformation Custom Transformers Transformation Pipelines Select and Train a Model Train and Evaluate on the Training Set Better Evaluation Using Cross-Validation Fine-Tune Your Model
Grid Search Randomized Search Ensemble Methods Analyzing the Best Models and Their Errors Evaluate Your System on the Test Set Launch，Monitor,and Maintain Your System TryItout Exercises 3．Classification MNIST Training a Binary Classifier Performance Measures Measuring Accuracy Using Cross-Validation Confusion Matrices Precision and Recall The Precision／Recall Trade-off The ROC Curve Multiclass Classification Error Analysis Multilabel Classification Multioutput Classification Exercises …… Part Ⅱ Neural Networks and Deep Learning A．Machine Learning Project Checklist B．Autodiff C．SpecialData Structures D．TensorFIowGraphs lndex
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