Deep Learning for Visual Computing (NPTEL Online Course) – Dr. Debdoot Sheet (IIT Kharagpur).
Lec01 Introduction to Visual Computing.
Lec02 Feature Extraction for Visual Computing.
Lec03 Feature Extraction with Python (Hands on).
Lec04 Neural Networks for Visual Computing.
Lec05 Classification with Perceptron Model (Hands on).
Lec06 Introduction to Deep Learning with Neural Networks (Part 1).
Lec07 Introduction to Deep Learning with Neural Networks (Part 2).
Lec08 Multilayer Perceptron and Deep Neural Networks (Part 1).
Lec09 Multilayer Perceptron and Deep Neural Networks (Part 2).
Lec10 Classification with Multilayer Perceptron (Hands on).
Lecture 11: Autoencoder for Representation Learning and MLP Initialization.
Lec12 MNIST handwritten digits classification using auto encoders (Hands on).
Lec13 Fashion MNIST classification using auto encoders.
Lec14 ALL-IDB Classification using auto encoders.
Lec15 Retinal Vessel Detection using auto encoders (Hands on).
Lec16 Stacked Autoencoders.
Lec17 MNIST and Fashion MNIST Classification with Stacked Autoencoders (Hands on).
Lec18 Sparse and Denoising Autoencoders.
Lec19 Sparse Autoencoders for MNIST classification (Hands on).
Lec20 Denoising Autoencoders for MNIST classification (Hands on).
Lecture 21 : Cost Function.
Lecture 22 : Classification cost functions.
Lecture 24 : Gradient Descent Learning Rule.
Lecture 25 : SGD and ADAM Learning Rules.Lecture 42 : Assessing the space and computational complexity of very deep CNNs.