Throughout the course, I learned about several machine learning concepts and how to apply them through weekly Python labs and 3 larger projects. These projects included k-nearest neighbor classification, linear regression, and clustering.
The class covered many fundamental machine learning topics, including:
- Data preprocessing
- Dimensionality Reduction
- Single and Multivariable Regression
- Classification
- Ensemble Methods
- Nearest Neighbors
- Clustering
- Association Analysis
- Neural Networks
- Recommender Systems