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Front Matter

Title Page
Contents
Chapter Topics
Preface

Part I. Fundamentals

Part I. Fundamentals
1. Introduction
2. Python Basics

Part II. Working with Data

Part II. Working with Data
3. NumPy Arrays
4. Pandas

Part III. Data Visualization

Part III. Data Visualization
5. Visualization
6. Matplotlib
7. Seaborn

Part IV. Inferential Statistics

Part IV. Inferential Statistics
8. Probability and Statistics
9. Hypothesis Testing
10. Two Samples
11. Estimation
12. Regression

Part V. Machine Learning

Part V. Machine Learning
13. Multiple Regression
14. Classification
15. Clustering

Appendices

1. Course Tooling
2. Jupyter Setup

Bibliography

Bibliography

Index

Index

Repository
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Assignments

3.4. Assignments#

These assignments will help you practice and apply the ideas from Chapter 3.

3.4.1. Preview
3.4.2. Lab
3.4.3. Homework

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3.3. Random Number Generation

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3.4.1. Preview

By Tsangyao Chen

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