1. Courses
  2. CSC354

Machine Learning

  • Teacher
    Dr. Saeed ur Rehman
  • Category
    Computing
  • Course Code
    CSC354
  • Session
    Fall 2020

Course Material/Videos

Available Resources
15476 Lecture 1 - Introduction to Course, Class and Outline Video Notes
15477 Lecture 2 - Whats is Learning, Types, Learning Associations Application Video Notes
15820 Lecture 3 - Classification, Regression, Training, and Testing Data Video Notes
15821 Lecture 4 - Supervised Learning, Learning from Class example, Training and Testing, True positive, true negative, false positive, and false negative Video Notes
15824 Lecture 5 - Vapnik-Chervonenkis (VC) Dimension Probably Approximately Correct (PAC) Learning, Noise, Learning Multiple Classes Video Notes
16941 Lecture 6 - Regression, Model Selection, and Generalization, Dimensions of a Supervised Machine Learning Algorithm Video Notes
16942 Lecture 7 - Introduction Classification Losses and Risks Video Notes
16943 Lecture 8 - Discriminant Functions Utility Theory Association Rules Video Notes
16944 Lecture 9 - Parametric Methods, Introduction, What are parametric methods/algorithms, Benefits and limitations of Parametric Algorithms MLE Video Notes
16949 Lecture 10 - Parametric methods revisited, Bayes theory, uses applications Video Notes
16950 Lecture 10 - Parametric methods revisited, Bayes theory, uses applications Video Notes
18918 Lecture 12 - Design and Analysis of Machine learning Experiment Video Notes
18919 Lecture 13 - Design and analysis of ML ALgorithms Video Notes
18920 Lecture 15 - Revision after Mid Term Video Notes
18924 Lecture 16 - Multivariate Methods, Multivariate Data, Parameter Estimation, Estimation of Missing Values, Multivariate Normal Distribution, Video Notes
18925 Lecture 17 - Decision Trees, Types, Construction, Introduction, Univariate Trees, Classification Trees, Regression Trees 19 Rule extraction Video Notes
19911 Lecture 18 - Decision trees continued Video Notes
19912 Lecture 19 - Linear discrimination Video Notes
21688 Lecture 20 - Introduction to Neural Network, Structure of a brain Video Notes
21689 Lecture 21 - Multilayer Perceptron MLP as a Universal Approximator Backpropagation Algorithm Video Notes
21690 Lecture 22 - Sessional 2 Video Notes
21691 Lecture 23 - CLustering _1 Video Notes
21692 Lecture 24 - Clustering_2 Video Notes
21698 Lecture 26 - Kernel Machines Video Notes
21700 Lecture 27 - Kernel Machine-II Video Notes

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