Machine Learning (CS 564)

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Introduction, Logistic regression, Perceptron,
Generative learning algorithm: Support vector machines, Model selection and feature selection, Ensemble methods: Bagging, boosting, Random Forest;
Unsupervised learning: Clustering: K-means, EM; Mixture of Gaussians, Factor analysis, PCA (Principal components analysis).;
Active learning: Theoretical analysis, Committee-based active learning, Active learning from the crowd;
Collaborative filtering: Latent factor-based models and neighborhood models;
Introduction to Graphical Models (HMM, MEMM, CRF), Deep Learning: CNN, RNN, LSTM, GRU.

Reference Books:

  1.  T. Mitchell. Machine Learning. McGraw-Hill, 1997
    Machine Learning (
    Machine Learning textbook (
  2.  Christopher Bishop. Pattern recognition and machine learning. Springer Verlag, 2006.
    Pattern Recognition and Machine Learning (
  3.  Hastie, Tibshirani, Friedman. The elements of Statistical Learning Springer Verlag.
    The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition | SpringerLink (You can purchase this book from here)
  4.  Probability, Random Variables and Stochastic processes by Papoulis and Pillai, 4thEdition, Tata McGraw Hill Edition.
  5.  A. K. Jain and R. C. Dubes. Algorithms for Clustering Data. Prentice Hall, 198815.


(You may need to login into IITP LMS for some classes. Better to login in one tab and then access these resources)

Lecture #Link to ClassTopic CoveredRemarks
1Class : 29 July 2023Introduction to ML
2Class :17 May 2023
3Class : 31 July 2023Introduction to Supervised, Unsupervised, Reinforcement Learning
4Class : 3 Aug 2023
Weekend Class : 5 Aug 2023
5Class : 7 Aug 2023Cluster Analysis: Basic Concept & Analysis
Types of Clusters
k-mean, SSE
6Class : 9 Aug 2023K-means in detail
7Class : 10 Aug 2023K-means, K-medoids
Weekend Class : 12 Aug 2023
8Class : 14 Aug 2023Hierarchical Clustering, Agglomerative Algorithm
9Class : 16 Aug 2023Hierarchical Clustering, DBSCAN
10Class : 17 Ag 2023DBSCAN
Weekend Class : 20 Aug 2023
Weekend Class : 20 Aug 2023
11Class : 21 Aug 2023DBSCAN
12Class : 23 Aug 2023
13Class : 24 Aug 2023
Weekend Class: 26 Aug 2023
14Class : 28 Aug 2023
15Class : 30 Aug 2023
16Class : 31 Aug 2023
Weekend Class: 2 Sep 2023

Topic wise Learning Material:

K-MeanMachine Intelligence – Lecture 7 (Clustering, k-means, SOM) – YouTube — very good explanation
K Means Clustering Algorithm | Edureka – YouTube
K Means Clustering Algorithm | Simplilearn – YouTube
K-Mediod & DBSCANIITM – Lec-27 K-Medoids and DBSCAN – YouTube
Supervised, Unsupervised, Reinforcement LearningSupervised vs Unsupervised vs Reinforcement Learning | Simplilearn – YouTubeIntroduction with examples

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