ACM Summer School on Algorithmic and Theoretical Aspects of Machine Learning (USB)

Media Storage Type : 32 GB USB Stick

NPTEL Subject Matter Expert : Meenakshi D'Souza

NPTEL Co-ordinating Institute : IIT Madras

NPTEL Lecture Count : 47

NPTEL Course Size : 12 GB

NPTEL PDF Text Transcription : Available and Included

NPTEL Subtitle Transcription : Available and Included (SRT)

Lecture Titles:

Lecture 1 - Learning on Finite State Automata and Decision Session - 1
Lecture 2 - Learning on Finite State Automata and Decision Session - 2
Lecture 3 - Learning on Finite State Automata and Decision Session - 3
Lecture 4 - Probability Session - 1
Lecture 5 - Probability Session - 2
Lecture 6 - Probability Session - 3
Lecture 7 - Probability Session - 4
Lecture 8 - Probability Session - 5
Lecture 9 - Probability Session - 6
Lecture 10 - Probability Session - 7
Lecture 11 - Probability Session - 8
Lecture 12 - Probability Session - 9
Lecture 13 - Probability Session - 10
Lecture 14 - Algebra for Machine Learning Session - 1
Lecture 15 - Algebra for Machine Learning Session - 2
Lecture 16 - Algebra for Machine Learning Session - 3
Lecture 17 - Crptography and Machine Learning
Lecture 18 - Neural Networks Session - 1
Lecture 19 - Neural Networks Session - 2
Lecture 20 - Neural Networks Session - 3
Lecture 21 - Neural Networks Session - 4
Lecture 22 - Neural Networks Session - 5
Lecture 23 - Enterprise Applications of ML Session - 1
Lecture 24 - Basic of Algorithm Design Session - 1
Lecture 25 - Basic of Algorithm Design Session - 2
Lecture 26 - Basic of Algorithm Design Session - 3
Lecture 27 - Basic of Algorithm Design Session - 4
Lecture 28 - Introduction to Optimization Session - 1
Lecture 29 - Introduction to Optimization Session - 2
Lecture 30 - Introduction to Reinforcement Learning Session - 1
Lecture 31 - Introduction to Reinforcement Learning Session - 2
Lecture 32 - Introduction to Reinforcement Learning Session - 3
Lecture 33 - Introduction to Reinforcement Learning Session - 4
Lecture 34 - Introduction to Reinforcement Learning Session - 5
Lecture 35 - Introduction to Reinforcement Learning Session - 6
Lecture 36 - Introduction to Reinforcement Learning Session - 7
Lecture 37 - Introduction of Cryptography Session - 1
Lecture 38 - Introduction of Cryptography Session - 2
Lecture 39 - Introduction of Cryptography Session - 3
Lecture 40 - Compressive Sensing Session - 1
Lecture 41 - Compressive Sensing Session - 2
Lecture 42 - Compressive Sensing Session - 3
Lecture 43 - Compressive Sensing Session - 4
Lecture 44 - Compressive Sensing Session - 5
Lecture 45 - Compressive Sensing Session - 6
Lecture 46 - Compressive Sensing Session - 7
Lecture 47 - Compressive Sensing Session - 8