Course10610624682 lectures
ACM India – RBCDSAI Summer School on DS/AI/ML (For Women Only) Hosted by PSG College of Technology, Coimbatore
IIT Madras
Lectures
week-01
- Introduction to AI/ML/DS
- Introduction to Probability; Introduction to machine learning Part 1
- Introduction to Probability; Introduction to machine learning Part 2
- Introduction to Probability; Introduction to machine learning Part 3
- Introduction to Probability; Introduction to machine learning Part 4
- Python for AI/ML/DS Part 1
- Python for AI/ML/DS Part 2
week-02
- Descriptive statistics and Inferential statistics Part 1
- Descriptive statistics and Inferential statistics Part 2
- Descriptive statistics and Inferential statistics Part 3
- Descriptive statistics and Inferential statistics Part 4
- Descriptive statistics and Inferential statistics Part 5
- Distribution, Data visualization, Plotting libraries Part 1
- Distribution, Data visualization, Plotting libraries Part 2
- Distribution, Data visualization, Plotting libraries Part 3
week-03
- Linear Algebra for Data science
- Identification of linear relationship among attributes
- Solving Linear Equations 1
- Solving Linear Equations 2
- Linear Algebra - Distance, Hyperplanes and Halfspaces, Eigenvalues, Eigenvectors Part 1
- Linear Algebra - Distance, Hyperplanes and Halfspaces, Eigenvalues, Eigenvectors Part 2
- Linear Algebra Part 1
- Linear Algebra Part 2
- Linear Algebra Part 3
week-04
- Regression Models, Models Selection & Evaluation Part 1
- Regression Models, Models Selection & Evaluation Part 2
- Regression Models, Models Selection & Evaluation Part 3
- Regression Models, Models Selection & Evaluation Part 4
- Regression Part 1
- Regression Part 2
- Regression Part 3
week-05
- Classification Naive Bayes, Logistic Regression, K-NN Part 1
- Classification Naive Bayes, Logistic Regression, K-NN Part 2
- Classification Naive Bayes, Logistic Regression, K-NN Part 3
- Classification Naive Bayes, Logistic Regression, K-NN Part 4
- Classification - Part 1
- Classification - Part 2
- Classification - Part 3
week-06
- Linear Models for Classification Part 1
- Linear Models for Classification Part 2
- Kernel Machines
- Solving Langrange Dual in SVM
- Classification and SVM Part 1
- Classification and SVM Part 2
week-07
- Tree - Based methods, Boosting bagging Part 1
- Tree - Based methods, Boosting bagging Part 2
- Tree - Based methods, Boosting bagging Part 3
- Tree - Based methods, Boosting bagging Part 4
- Tree-based approaches for regression and classification Part 1
- Tree-based approaches for regression and classification Part 2
week-08
- Supervised Learning Using K Nearest Neighbors Part 1
- Supervised Learning Using K Nearest Neighbors Part 2
- Supervised Learning Using K Nearest Neighbors Part 3
- Supervised Learning Using K Nearest Neighbors Part 4
- Clustering methods Part 1
- Clustering methods Part 2
week-09
- Induction to Neural Networks, Perceptrons, Multilayer Perceptrons, Feedforward Neural Networks Part1
- Induction to Neural Networks, Perceptrons, Multilayer Perceptrons, Feedforward Neural Networks Part2
- Induction to Neural Networks, Perceptrons, Multilayer Perceptrons, Feedforward Neural Networks Part3
- Induction to Neural Networks, Perceptrons, Multilayer Perceptrons, Feedforward Neural Networks Part4
- Neural Networks and Feedforward NN Part 1
- Neural Networks and Feedforward NN Part 2
- Neural Networks and Feedforward NN Part 3
week-10
- Backpropagation (Intuition)
- Backpropagation: Computing Cradients w.r.t the Output Units
- Learning Parameters: Gradient Descent
- Contours
- Nesterov Accelerated Gradient Descent
- Stochastic and Mini-Batch Gradient Descent
- Tips for Adjusting learning Rate and Momentum
- Line Search
- The convolution operation
- Convolutional Neural Networks
- CNN and DL models Part 1
- CNN and DL models Part 2
- CNN and DL models Part 3
- CNN and DL models Part 4
week-11
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Madras
- Department
- Computer Science and Engineering
- Level
- Undergraduate
- Language
- English
- Subjects
- Computer science, Engineering
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed
More like this
NPTEL113106082
Course
Welding of Advanced High Strength Steels for Automotive Applications
20 lectures · Video
NPTEL101106082
Course
Rocket Propulsion
36 lectures · Source's player
NPTEL101106031
Course
Acoustic Instabilities in Aerospace Propulsion
41 lectures · Video
NPTEL101106033
Course
Aerospace Propulsion
42 lectures · Video
NPTEL101106037
Course
Combustion
51 lectures · Video
NPTEL101106042
Course
Flight Dynamics II (Stability)
41 lectures · Video
NPTEL101106044
Course
Gas Dynamics
54 lectures · Video
NPTEL101106045
Course
Introduction to CFD
39 lectures · Video
NPTEL105106204
Course
Colloids and Surfaces
48 lectures · Source's player
NPTEL105106205
Course
Polymers: Concepts, Properties, Uses and Sustainability
87 lectures · Source's player
NPTEL103106158
Course
Fluid And Particle Mechanics
73 lectures · Source's player
NPTEL103106220
Course
Artificial Lift
62 lectures · Source's player