Machine Learning

J.-S. Roger Jang, CSIE Dept., National Taiwan University


  1. Math & Optimization
    1. Gradient descent: (EMBA-week01)
    2. Genetic algorithms:
    3. Simulated annealing:
    4. Downhill simplex search:
    5. Random search
    6. Tabu search
    7. Jensen's inequality:
    8. Linear combination of random variables:
  2. Fundamentals of Machine Learning (ML)
    1. Intro to AI: (EMBA-week01)
    2. AI's dilemma: (EMBA-week01)
    3. Intro to ML: (EMBA-week01)
    4. Datasets for ML:
    5. Supervised learning
      • K-nearest-neightbor classifiers: (EMBA-week01)
      • Linear classifiers: (EMBA-week01)
      • Naive Bayes classifiers:
      • Quadratic classifiers:
      • GMMC:
      • SLP:
      • MLP & DNN:
      • Backpropagation:
      • SVM
    6. Unsupervised learning (Clustering)
      • K-mean clustering:
      • Fuzzy c-mean clustering:
      • Hierarchical clustering:
    7. Density estimation
      • Maximum likelihood estimate (MLE):
      • Gaussian mixture models (GMM)
      • Hidden Markov models (HMM):
    8. Dimensionality reduction
      • Feature selection:
      • Feature extraction
        • PCA:
        • LDA
    9. Distance metrics and loss functions
    10. Dynamic programming
      • Intro to dynamic programming (DP):
      • DP for longest common subsequence (LCS):
      • DP for edit distance (ED):
      • DP for matrix chain product (MCP):
      • Dynamic time warping (DTW):
    11. Performance indices
      • ROC & DEC (old version):
      • Performance indices:
    12. Performance evaluation
      • K-fold cross-validation:
    13. Walkthrough
      • A walkthrough of machine learning for leaf identification:
  3. Advaced Topics in Machine Learning
    1. More models
    2. Start your AI group
  4. Unstructured Data in Machine Learning
    1. Chinese word segmentation: (EMBA-week02)
    2. Document classification: (EMBA-week02)
  5. Applications of Machine Learning
    1. Manufacturing
    2. Audio processing
      • Intro to audio signals:
      • Basic audio features:
      • Pitch tracking in time domain:
      • Singing voice separation (a short version for children):
      • Source separation in music
      • Speaker verification/identification
    3. Image recognition
    4. FinTech
      • Candlestick chart (K線圖):
      • Intro to stock prediction:
      • Technical analysis (including MA):
      • Technical indicator of RSI:
      • DP for trading (when stock price is fully known in advance):
      • Sharpe ratio:
      • Portfolio optimization:
      • 金融擁抱 AI 的機會與挑戰:
      • AI 專案在金融場景的美麗與哀愁:
      • AI for FinTech (EMBA-week02)
      • Fintech examples
      • Precision sales
    5. Chatbots
    6. Fuzzy sets and fuzzy logic
      • Fuzzy sets (a short version for children):
  6. Summary and demos
    1. SOP for machine learning (EMBA-week02)
    2. Summary of ML (EMBA-week02)
    3. Project summary at MIR Lab (EMBA-week02)
    4. Demos at MIR Lab
  7. Tutorials on specific topics
    1. Fatty liver detection
    2. Anomaly sound detection
    3. Leaf identification