19_Course_Summary

# 19: Course Summary

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Index
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