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Preface vii
Chapter 1: Gearing Up for Predictive Modeling 1
Models 1
Learning from data 3
The core components of a model 7
Our fist model: k-nearest neighbors 8
Types of models 10
Supervised, unsupervised, semi-supervised, and reinforcement
learning models 11
Parametric and nonparametric models 12
Regression and classifiation models 13
Real-time and batch machine learning models 14
The process of predictive modeling 14
Defiing the model's objective 15
Collecting the data 16
Picking a model 18
Preprocessing the data 19
Exploratory data analysis 19
Feature transformations 20
Encoding categorical features 23
Missing data 25
Outliers 26
Removing problematic features 26
Feature engineering and dimensionality reduction 29
Training and assessing the model 33
Repeating with different models and fial model selection 38
Deploying the model 38
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