Machine Learning by professor Andrew Ng in Coursera

Summary

Summary: Main topics

• Supervised Learning
  • Linear regression, logistic regression, neural networks, SVMs
• Unsupervised Learning
  • K-means, PCA, Anomaly detection
• Special applications/special topics
  • Recommender systems, large scale machine learning
• Advice on building a machine learning system
  • Bias/variance, regularization; deciding what to work on next: evaluation of learning algorithms, learning curves, error analysis, ceiling analysis.