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Part I. Introduction

Part II. Python Basics

Part III. Working with Data

Part IV. Data Visualization

Part V. Inferential Statistics

14. Probability and Statistics
- 14.1. Descriptive Statistics & Distribution
- 14.2. Sampling Variability
15. Testing Hypothesis
16. Comparing Two Samples
17. Estimation
18. Prediction with Regression

Part VI. Machine Learning

19. Machine Learning
20. Multiple Regression
- 20.5. Linear Regression
- 20.6. Multiple Regression
21. Classification
22. Introduction to Clustering
- 22.5. K Means Clustering with Python
- 22.6. K Means Clustering with Python

Appendices

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By Tsangyao Chen