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Getting Started with Scikit-Learn

Chapter 1: Introduction to Scikit-learn and Setup

What is Scikit-learn?

Installation and Environment Setup

Overview of the Scikit-learn API

Data Representation in Scikit-learn

Loading Example Datasets

Hands-on Practical: Setup Verification

Chapter 2: Supervised Learning: Regression

Introduction to Regression Problems

Linear Regression Fundamentals

Implementing Linear Regression with Scikit-learn

Interpreting Model Coefficients

Regression Evaluation Metrics

Calculating Metrics in Scikit-learn

Hands-on Practical: Building a Regression Model

Chapter 3: Supervised Learning: Classification

Introduction to Classification Problems

Logistic Regression for Classification

K-Nearest Neighbors (KNN) Algorithm

Implementing KNN with Scikit-learn

Support Vector Machines (SVM) Basics

Implementing SVM with Scikit-learn

Classification Evaluation Metrics

Calculating Metrics in Scikit-learn

Hands-on Practical: Building Classification Models

Chapter 4: Data Preprocessing and Feature Engineering

The Importance of Data Preprocessing

Feature Scaling Techniques

Applying Scalers in Scikit-learn

Encoding Categorical Features

Applying Encoders in Scikit-learn

Handling Missing Values

Using Imputers in Scikit-learn

Hands-on Practical: Preprocessing Data

Chapter 5: Model Selection and Evaluation

The Problem of Overfitting and Underfitting

Splitting Data: Training and Testing Sets

Introduction to Cross-Validation

Implementing K-Fold Cross-Validation

Stratified K-Fold for Classification

Grid Search for Hyperparameter Tuning

Hands-on Practical: Model Evaluation and Selection

Chapter 6: Building Pipelines

Motivation for Using Pipelines

Creating a Simple Pipeline

Accessing Pipeline Steps

Using Pipelines with Cross-Validation

Grid Search with Pipelines

Constructing Complex Pipelines with ColumnTransformer

Hands-on Practical: Pipeline Construction and Tuning

Introduction to Scikit-learn and Setup

Sections

1.1 What is Scikit-learn?
1.2 Installation and Environment Setup
1.3 Overview of the Scikit-learn API
1.4 Data Representation in Scikit-learn
1.5 Loading Example Datasets
1.6 Hands-on Practical: Setup Verification

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