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TABLE OF CONTENTS16 sections

Machine Learning Basics

01Machine Learning Basics 02Foundations And Landscape Of Machine Learning 03Mathematical And Statistical Foundations 04Problem Framing And The Machine Learning Lifecycle 05Data Preparation And Feature Engineering 06Regression Models 07Classification Models 08Model Evaluation Selection And Tuning 09Unsupervised Learning And Dimensionality Reduction 10Ensemble Learning 11Neural Networks And Deep Learning Foundations 12Applied Machine Learning Workflows And Tools 13Deployment Mlops And Model Monitoring 14Explainable Ethical And Secure Machine Learning 15Decision Analytics Management And Digital Transformation 16Emerging Trends And Future Directions

Chapter 1

Foundations And Landscape Of Machine Learning

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