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Machine Learning Intro Course Materials

Introduction to Python

1. Introduction to Python

Recap Statistics

2. Recap Statistics
- 2.3. Additional Exercises III - The Normal distribution

Feature Scales

3. Feature Scales
- 3.4. Additional Exercises IV - Feature Scales

Recap Regression & Correlation

4. Linear Regression
5. Correlation and Regression
- 5.2. Additional Exercises V - Regression & Correlation

Time Series Analysis

6. Time Series Analysis

Machine Learning Algorithms

7. Machine learning Algorithms I
8. Supervised Machine Learning
9. Unsupervised Machine Learning
- 9.1. Clustering Algorithms - \(k\)-Means

Neural Networks

10. Multilayer perceptron (MLP) - the Machine Learning Workflow

References

References

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.ipynb

Unsupervised Machine Learning

9. Unsupervised Machine Learning#

unsupervised_overview

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8.4. Random Forest Regression

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9.1. Clustering Algorithms - \(k\)-Means

By Annette Rudolph, Marie-Christin Eckert

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