Modules / Lectures

Video Transcript:

Auto Scroll Hide
Module NameDownload
noc20_cs49_assigment_1noc20_cs49_assigment_1
noc20_cs49_assigment_2noc20_cs49_assigment_2
noc20_cs49_assigment_3noc20_cs49_assigment_3
noc20_cs49_assigment_4noc20_cs49_assigment_4
noc20_cs49_assigment_5noc20_cs49_assigment_5
noc20_cs49_assigment_6noc20_cs49_assigment_6
noc20_cs49_assigment_7noc20_cs49_assigment_7


Sl.No Chapter Name MP4 Download
1Introduction to the Machine Learning CourseDownload
2Foundation of Artificial Intelligence and Machine Learning Download
3Intelligent Autonomous Systems and Artificial IntelligenceDownload
4Applications of Machine LearningDownload
5Tutorial for week01Download
6Characterization of Learning ProblemsDownload
7Objects, Categories and FeaturesDownload
8Feature related issuesDownload
9Scenarios for Concept LearningDownload
10Tutorial for week02Download
11Forms of RepresentationDownload
12Decision TreesDownload
13Bayes (ian) Belief NetworksDownload
14Artificial Neural NetworksDownload
15Tutorial for week03Download
16Genetic algorithmDownload
17Logic ProgrammingDownload
18Inductive Learning based on Symbolic Representations and Weak TheoriesDownload
19Generalization as Search - Part 01Download
20Generalization as Search - Part 02Download
21Decision Tree Learning Algorithms - Part 01Download
22Decision Tree Learning Algorithms - Part 02Download
23Instance Based Learning - Part 01Download
24Instance Based Learning - Part 02Download
25Cluster AnalysisDownload
26Tutorial for week04Download
27Machine Learning enabled by Prior TheoriesDownload
28Explanation Based LearningDownload
29Inductive Logic ProgrammingDownload
30Reinforcement Learning - Part 01 IntroductionDownload
31Reinforcement Learning - Part 02 Learning AlgorithmsDownload
32Reinforcement Learning - Part 03 Q - LearningDownload
33Case - Based ReasoningDownload
34Tutorial for week05Download
35Fundamentals of Artificial Neural Networks - Part1Download
36Fundamentals of Artificial Neural Networks - Part2Download
37PerceptronsDownload
38Model of Neuron in an ANNDownload
39Learning in a Feed Forward Multiple Layer ANN - BackpropagationDownload
40Recurrent Neural NetworksDownload
41Hebbian Learning and Associative MemoryDownload
42Hopfield Networks and Boltzman Machines - Part 1Download
43Hopfield Networks and Boltzman Machines - Part 2Download
44Convolutional Neural Networks - Part 1Download
45Convolutional Neural Networks - Part 2Download
46DeepLearningDownload
47Tutorial for week05 Download
48Tools and ResourcesDownload
49Interdisciplinary InspirationDownload
50Preparation for Exam and Example of ApplicationsDownload

Sl.No Chapter Name English
1Introduction to the Machine Learning CoursePDF unavailable
2Foundation of Artificial Intelligence and Machine Learning PDF unavailable
3Intelligent Autonomous Systems and Artificial IntelligencePDF unavailable
4Applications of Machine LearningPDF unavailable
5Tutorial for week01PDF unavailable
6Characterization of Learning ProblemsPDF unavailable
7Objects, Categories and FeaturesPDF unavailable
8Feature related issuesPDF unavailable
9Scenarios for Concept LearningPDF unavailable
10Tutorial for week02PDF unavailable
11Forms of RepresentationPDF unavailable
12Decision TreesPDF unavailable
13Bayes (ian) Belief NetworksPDF unavailable
14Artificial Neural NetworksPDF unavailable
15Tutorial for week03PDF unavailable
16Genetic algorithmPDF unavailable
17Logic ProgrammingPDF unavailable
18Inductive Learning based on Symbolic Representations and Weak TheoriesPDF unavailable
19Generalization as Search - Part 01PDF unavailable
20Generalization as Search - Part 02PDF unavailable
21Decision Tree Learning Algorithms - Part 01PDF unavailable
22Decision Tree Learning Algorithms - Part 02PDF unavailable
23Instance Based Learning - Part 01PDF unavailable
24Instance Based Learning - Part 02PDF unavailable
25Cluster AnalysisPDF unavailable
26Tutorial for week04PDF unavailable
27Machine Learning enabled by Prior TheoriesPDF unavailable
28Explanation Based LearningPDF unavailable
29Inductive Logic ProgrammingPDF unavailable
30Reinforcement Learning - Part 01 IntroductionPDF unavailable
31Reinforcement Learning - Part 02 Learning AlgorithmsPDF unavailable
32Reinforcement Learning - Part 03 Q - LearningPDF unavailable
33Case - Based ReasoningPDF unavailable
34Tutorial for week05PDF unavailable
35Fundamentals of Artificial Neural Networks - Part1PDF unavailable
36Fundamentals of Artificial Neural Networks - Part2PDF unavailable
37PerceptronsPDF unavailable
38Model of Neuron in an ANNPDF unavailable
39Learning in a Feed Forward Multiple Layer ANN - BackpropagationPDF unavailable
40Recurrent Neural NetworksPDF unavailable
41Hebbian Learning and Associative MemoryPDF unavailable
42Hopfield Networks and Boltzman Machines - Part 1PDF unavailable
43Hopfield Networks and Boltzman Machines - Part 2PDF unavailable
44Convolutional Neural Networks - Part 1PDF unavailable
45Convolutional Neural Networks - Part 2PDF unavailable
46DeepLearningPDF unavailable
47Tutorial for week05 PDF unavailable
48Tools and ResourcesPDF unavailable
49Interdisciplinary InspirationPDF unavailable
50Preparation for Exam and Example of ApplicationsPDF unavailable


Sl.No Language Book link
1EnglishNot Available
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available