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TABLE OF CONTENTS16 sections

Supervised & Unsupervised Learning

01Supervised & Unsupervised Learning 02Foundations Of Statistical And Machine Learning 03Business Problem Formulation And Analytics Workflow 04Data Preparation And Feature Engineering 05Regression And Regularized Predictive Models 06Classification And Probability Estimation 07Decision Trees And Ensemble Learning 08Margin Based Kernel And Neural Learning 09Model Evaluation Selection And Tuning 10Clustering And Business Segmentation 11Dimensionality Reduction And Latent Structure 12Association Pattern Discovery And Anomaly Detection 13Explainability And Decision Centered Analytics 14Deployment Mlops And Scalable Learning Systems 15Ethics Risk And Machine Learning Governance 16Enterprise Applications And Emerging Directions

Chapter 5

Classification And Probability Estimation

PREVIOUS SECTIONRegression And Regularized Predictive Models UP NEXTDecision Trees And Ensemble Learning

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