The Applied Data Science Workshop

封面

版权信息

Preface

1. Introduction to Jupyter Notebooks

Introduction

Basic Functionality and Features of Jupyter Notebooks

Jupyter Features

Summary

2. Data Exploration with Jupyter

Introduction

Our First Analysis – the Boston Housing Dataset

Summary

3. Preparing Data for Predictive Modeling

Introduction

Machine Learning Process

Approaching Data Science Problems

Understanding Data from a Modeling Perspective

Introducing the Human Resource Analytics Dataset

Summary

4. Training Classification Models

Introduction

Understanding Classification Algorithms

Summary

5. Model Validation and Optimization

Introduction

Assessing Models with k-Fold Cross Validation

Dimensionality Reduction with PCA

Summary

6. Web Scraping with Jupyter Notebooks

Introduction

Internet Data Sources

Introduction to HTTP Requests

Data Workflow with pandas

Summary

Appendix

1. Introduction to Jupyter Notebooks

2. Data Exploration with Jupyter

3. Preparing Data for Predictive Modeling

4. Training Classification Models

5. Model Validation and Optimization