CS6140/4420 Machine Learning, Summer 2025 Online

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* Schedule and materials subject to change
Week / Module Topic / Lecture Other Reading Assignment
  • 5/7 - 5/14
  • Week 1 / Module 1: Intro, Decision Tree
  • Course Map

  • Topics:
  • Administrative
  • Intro to ML, Matrix Data
  • Rule-based Classifiers
  • Decision/Regression Trees
  • Linear Regression
  • 5/14 - 5/21
  • Topics:
  • Setup, Cross Validation
  • Error, Accuracy, ROC, AUC


Notes: Ridge Regression (normal equations)




  • 5/21 - 5/28
  • Topics:
  • Gradient Descent
  • Linear Regression with GD
  • Logistic Regression
  • Newton Method
  • DHS ch 5
  • KMPP ch 7, 8
  • 5/28 - 6/4
  • Topics:
  • Perceptrons
  • Neural Networks


  • DHS ch 6
  • 6/4 - 6/11
  • Topics:
  • Probabilities as data densities
  • Maximum Likelihood, fit params to data
  • Gaussian Discriminant Analysis
  • Naive Bayes

  • DHS ch 2, 3
  • KMPP ch 2, 3, 4
  • 6/11 - 6/18
  • Topics:
  • EM algorithm for fitting mixtures
  • Graphical Models

  • 6/18 - 6/25
  • Topics:
  • Online Learning
  • Adaboost Algorithm
  • Bagging
  • RankBoost, Gradient Boosting


  • 6/25 - 7/2
  • Topics:
  • Active Learning and VC Dimension
  • Multiclass ECOC


  • DHS ch 9.5
  • KMPP ch 16.6
  • KMPP ch 27.6.2
  • 7/2 - 7/9
  • Topics:
  • Margins, Boosting Feature Analysis
  • PCA and LDA, Lagrangian Multipliers
  • Regularized Regression RIDGE and LASSO
  • Missing Values
  • Independence Day : no class/OH
    July 4

PrincipalComponent Analysis (slides, sceencast)
Missing Values and Naive Bayes

optional: Fischer LDA
Slides: tSNE / paper / implementation
optional: tSNE gradient calculation
  • PCA: DHS ch 10
  • KMPP ch 25
  • 7/9 - 7/16
  •  
  • Topics:
  • Support Vector Machines
  • Duality with KKT conditions
  • Maximizing Margins Constrained Optimization
  • SMO Algorithm


  • DSH ch 5.11
  • KMPP ch 14
  • 7/16 - 7/23
  • Topics:
  • Kernels
  • Kernels for SVM
  • K-Nearest Neighbor
  • Kernel Similarity and KNN
  • Kernel Density Estimation
  • Heat Kernels, Harmonic Equation

paper: Kernel Methods in Machine Learning

  • Learning with harmonic functions



    • 7/23 - 7/30
    •    
    • Topics:
    • Adv NN
    • RNN
    • TRN




    • 7/30 - 8/6

    • Topics:
    • TRN, attention

    • 8/8

    • Week 14 Project

    Project Report due Fri 8/8

    • 8/6 - 8/13

    • Topics:
    • TRN, attention