aiacademy: 機器學習 - 實作: ch09 (unsupervised learning)

Principlal Component analysis (PCA)

from sklean.decomposition import PCA

t-SEN

K-means

Machine Learning - Summary

What we have learned

• We mostly discussed supervised learning

  • Linear regression
  • Logistic regression
  • SVM
  • KNN
  • Decision Trees
  • random forest
  • AdaBoost
  • Gradient Boosting
  • etc.

• We also discussed a few unsupervised learning methods

  • PCA
  • t-SNE
  • K-means
  • hierachical clustering

What was not covered (but probably important if you want to dive deeper in AI/ML)

• Deep Learning
• Reinforcement learning
• Bayesian learning
• Numerical optimization
• Searching
• Knowledge representataion