Machine Learning

Lectures:

• Course Outline
• 16-06-14 Lecture-1 Introduction PDF
• 17-06-14 Data Normalization, KNN, Minimum distance PDF
• 24-06-14 Lecture-3 Perceptron PDF
• 08-07-14 Lecture-4 MLP & Decision Trees PDF
• 15-07-14 Lecture-5 Decision Trees for Numeric Data PDF
• 18-07-14 Lecture-6 Naive Bayes PDF
• 18-07-14 Grade Sheet PDF
• 05-08-14 Lecture-7 Bayes Decision Theory-I PDF
• 18-08-14 Lecture-8 Bayes Decision Theory-II PDF
• 05-12-14 Lecture-9 Dimensionality Reduction PDF
• 22-08-14 Lecture-10 Feature Selection PDF
• 02-09-14 Lecture-11 Clustering PDF
• 11-09-14 Lecture-12 HMM PDF
• 18-09-14 Guest Lecture PDF
• 18-09-14 Guest Lecture (SOM) PDF
• 21-09-14 Project Presentations (25 Sept) PDF

Assignments:

• 19-06-14 Assignment-I PDF
• 19-06-14 Dataset for Assignment-1 XLS
• 21-07-14 Assignment-2 ZIP
• 27-07-14 Mini Project PDF
• 13-08-14 Assignment-3 PDF