31:15Cancer Image Analysis using AI: Opportunities and Challenges
A 31-minute video from Amit Sethi: “Cancer Image Analysis using AI: Opportunities and Challenges”.
Amit Sethi
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31:15
58:29EE769 1 1 Introduction to Machine Learning
A 58-minute video from Amit Sethi: “EE769 1 1 Introduction to Machine Learning”.
31:24EE769 1 3 Intro to Intro to ML
A 31-minute video from Amit Sethi: “EE769 1 3 Intro to Intro to ML”.
10:13EE769 2 1 Basic Math for ML - Module overview and vector operations
A 10-minute video from Amit Sethi: “EE769 2 1 Basic Math for ML - Module overview and vector operations”.
26:19EE769 2 10 Basic Math for ML - Continuous random variables
A 26-minute video from Amit Sethi: “EE769 2 10 Basic Math for ML - Continuous random variables”.
27:35EE769 2 11 Basic CS and Python for ML
A 28-minute video from Amit Sethi: “EE769 2 11 Basic CS and Python for ML”.
12:26EE769 2 2 Basic Math for ML - Vector subspaces and matrix operations
A 12-minute video from Amit Sethi: “EE769 2 2 Basic Math for ML - Vector subspaces and matrix operations”.
9:34EE769 2 3 Basic Math for ML - More matrix properties and matrix operations
A 10-minute video from Amit Sethi: “EE769 2 3 Basic Math for ML - More matrix properties and matrix operations”.
11:00EE769 2 4 Basic Math for ML - Pseudo inverse and eigen decomposition of matrices. Tensors.
A 11-minute video from Amit Sethi: “EE769 2 4 Basic Math for ML - Pseudo inverse and eigen decomposition of matrices. Tensors.”.
20:31EE769 2 5 Basic Math for ML - Functions of single variables and their basic characterization.
A 21-minute video from Amit Sethi: “EE769 2 5 Basic Math for ML - Functions of single variables and their basic characterization.”.
9:39EE769 2 6 Basic Math for ML - Intro to convex optimization using gradient descent on functions
A 10-minute video from Amit Sethi: “EE769 2 6 Basic Math for ML - Intro to convex optimization using gradient descent on functions”.
20:20EE769 2 7 Basic Math for ML - multivariate functions, their gradients and convex optimization.
A 20-minute video from Amit Sethi: “EE769 2 7 Basic Math for ML - multivariate functions, their gradients and convex optimization.”.
22:48EE769 2 8 Basic Math for ML - Discrete random variable, its PMF, and expectation
A 23-minute video from Amit Sethi: “EE769 2 8 Basic Math for ML - Discrete random variable, its PMF, and expectation”.
15:15EE769 2 9 Basic Math for ML - Entropy, and joint, conditional, marginal distributions
A 15-minute video from Amit Sethi: “EE769 2 9 Basic Math for ML - Entropy, and joint, conditional, marginal distributions”.
7:07EE769 3 1 Intro to Regression
Advanced
A 7-minute video from Amit Sethi: “EE769 3 1 Intro to Regression”.
34:24EE769 3 2 Bias and Variance Decomposition of Regression
Advanced
A 34-minute video from Amit Sethi: “EE769 3 2 Bias and Variance Decomposition of Regression”.
24:45EE769 3 3 Finding Solution of Linear Regression
Advanced
A 25-minute video from Amit Sethi: “EE769 3 3 Finding Solution of Linear Regression”.
23:22EE769 3 5 Regularizing Linear Regression
Advanced
A 23-minute video from Amit Sethi: “EE769 3 5 Regularizing Linear Regression”.
14:46EE769 4 1 Linear classification - Basics
Advanced
A 15-minute video from Amit Sethi: “EE769 4 1 Linear classification - Basics”.
24:35EE769 4 2 Linear classification - Motivation
Advanced
A 25-minute video from Amit Sethi: “EE769 4 2 Linear classification - Motivation”.
7:42EE769 4 3 Linear classification - Certain Bayesian classifiers are linear
Advanced
A 8-minute video from Amit Sethi: “EE769 4 3 Linear classification - Certain Bayesian classifiers are linear”.
11:07EE769 4 4 Linear classification - Perceptron algorithm
Advanced
A 11-minute video from Amit Sethi: “EE769 4 4 Linear classification - Perceptron algorithm”.
11:58EE769 4 5 Linear classification - Logistic regression
Advanced
A 12-minute video from Amit Sethi: “EE769 4 5 Linear classification - Logistic regression”.
26:26EE769 4 6 Linear classification - SVM
Advanced
A 26-minute video from Amit Sethi: “EE769 4 6 Linear classification - SVM”.
29:44EE769 5 1 Feature selection - motivation and creating new features
Advanced
A 30-minute video from Amit Sethi: “EE769 5 1 Feature selection - motivation and creating new features”.
14:14EE769 5 2 Feature selection - features for images
Advanced
A 14-minute video from Amit Sethi: “EE769 5 2 Feature selection - features for images”.
16:37EE769 5 3 Feature selection audio and text features
Advanced
A 17-minute video from Amit Sethi: “EE769 5 3 Feature selection audio and text features”.
11:38EE769 5 4 Feature selection - feature reduction 1 of 2
Advanced
A 12-minute video from Amit Sethi: “EE769 5 4 Feature selection - feature reduction 1 of 2”.
14:22EE769 5 5 Feature selection - feature reduction 2 of 2
Advanced
A 14-minute video from Amit Sethi: “EE769 5 5 Feature selection - feature reduction 2 of 2”.
14:09EE769 6 3 SVM - Dual form for soft SVM
Advanced
A 14-minute video from Amit Sethi: “EE769 6 3 SVM - Dual form for soft SVM”.
17:49EE769 6 4 SVM - SVM for Regression
Advanced
A 18-minute video from Amit Sethi: “EE769 6 4 SVM - SVM for Regression”.
1:07:04EE769 CNN lecture 3
A 67-minute video from Amit Sethi: “EE769 CNN lecture 3”.
1:22:43EE769 Intro to CNNs Lecture 2
A 83-minute video from Amit Sethi: “EE769 Intro to CNNs Lecture 2”.
22:53EE769-10-1 Clustering - K-means
Advanced
A 23-minute video from Amit Sethi: “EE769-10-1 Clustering - K-means”.
37:27EE769-10-2 Clustering - DBSCAN
A 37-minute video from Amit Sethi: “EE769-10-2 Clustering - DBSCAN”.
20:59EE769-10-3 Clustering - Clustering due diligence
Advanced
A 21-minute video from Amit Sethi: “EE769-10-3 Clustering - Clustering due diligence”.