ACM India Summer School on Algorithms for Data Science (2023)

Media Storage Type : 32 GB USB Stick

NPTEL Subject Matter Expert : Multi-Faculty

NPTEL Co-ordinating Institute : IIT Madras

NPTEL Lecture Count : 34

NPTEL Course Size : 7.2 GB

NPTEL PDF Text Transcription : Available and Included

NPTEL Subtitle Transcription : Available and Included (SRT)

Lecture Titles:

Lecture 1 - Introduction - ACM India Summer School on Algorithms for Data Science
Lecture 2 - Introducation to Probability
Lecture 3 - Selection Problems
Lecture 4 - Median from Read-Only Memory
Lecture 5 - Majority and Heavy Hitters
Lecture 6 - Introducation to ProbabilityTail inequalities
Lecture 7 - Chernoff Bounds
Lecture 8 - Quickselect and Quicksort
Lecture 9 - Introduction to Randomized Algorithms: Graph Minimum Cut
Lecture 10 - Introduction to Streaming Algorithm and Reservoir Sampling
Lecture 11 - Approximate Counting in Streaming: MORRIS Counter
Lecture 12 - Median of Means Technique Applied to Approximate Counting
Lecture 13 - Counting Distinct Elements in Streaming
Lecture 14 - 2-Universal Hashing and Applications for Derandomizing
Lecture 15 - Approximate Heavy Hitters
Lecture 16 - Frequency Moments
Lecture 17 - Graph Streaming Algorithms
Lecture 18 - Locality Sensitive Hashing - Part 1
Lecture 19 - Locality Sensitive Hashing - Part 2
Lecture 20 - Locality Sensitive Hashing - Part 3
Lecture 21 - Graph Streaming Lower Bounds
Lecture 22 - Bloom Filters
Lecture 23 - Frequent Pattern Mining - Part 1
Lecture 24 - Frequent Pattern Mining - Part 2
Lecture 25 - Is AI ready for The real world?
Lecture 26 - Online Learning and Multiarmed Bandits - Part 1
Lecture 27 - Online Learning and Multiarmed Bandits - Part 2
Lecture 28 - Reinforcement Learning - Part 1
Lecture 29 - Reinforcement Learning - Part 2
Lecture 30 - Singular Value Decomposition - Part 1
Lecture 31 - Singular Value Decomposition - Part 2
Lecture 32 - Graph Centralities
Lecture 33 - Johnson Lindenstrauss Lemma
Lecture 34 - Graph Centralities Clustering and Partition