1. About

About

• 1.1. Certificate
• 1.2. Description
• 1.3. Survey

2. Introduction

Introduction

• 2.1. What is Data?
• 2.2. Basic Statistics
• 2.3. Machine Learning Introduction
• 2.4. Glossary PL
• 2.5. Glossary
• 2.6. Datasets
• 2.7. Machine Learning Algorithms
• 2.8. Features
• 2.9. Classifiers

3. Sklearn

Sklearn

• 3.1. scikit-learn

4. Model Quality

Model Quality

• 4.1. Model Quality
• 4.2. Principal Component Analysis

5. Decision Trees

Decision Trees

• 5.1. Decision Tree

6. Regressions

Regressions

• 6.1. Linear Regression
• 6.2. Logistic Regression

7. K-Nearest Neighbors

K-Nearest Neighbors

• 7.1. K Nearest Neighbors

8. Bayes

Bayes

• 8.1. Naive Bayes

9. Support Vector Machines

Support Vector Machines

• 9.1. Support Vector Machines

10. Clustering

Clustering

• 10.1. K-Means Clustering

11. Neural Networks

Neural Networks

• 11.1. Deep Neural Network
• 11.2. Convolutional Neural Network

12. References

References

• 12.1. References

13. Articles

Articles

• 13.1. Machine Learning Introduction
• 13.2. Notes