19_Course_Summary

Summary of course topics

Supervised learning - labeled data
- Linear regression
- Logistic regression
- Neural networks
- Support vector machines
Unsupervised learning - unlabeled data
- K-means
- PCA
- Anomaly detection
Special applications/topics
- Recommender systems
- Large scale machine learning
Advice on building machine learning systems
- Bias and variance
- Regularization
- What to do next when developing a system
- Algorithm evaluation
- Learning curves
- Error analysis
- Ceiling analysis

19: Course Summary