Deep Learning - IITKGP
Indian Institute of Technology, Kharagpur and NPTEL via Swayam
-
30
-
- Write review
Overview
Syllabus
COURSE LAYOUT
Week 1: Introduction to Deep Learning, Bayesian Learning, Decision SurfacesWeek 2: Linear Classifiers, Linear Machines with Hinge LossWeek 3: Optimization Techniques, Gradient Descent, Batch OptimizationWeek 4: Introduction to Neural Network, Multilayer Perceptron, Back Propagation LearningWeek 5: Unsupervised Learning with Deep Network, AutoencodersWeek 6: Convolutional Neural Network, Building blocks of CNN, Transfer LearningWeek 7: Revisiting Gradient Descent, Momentum Optimizer, RMSProp, AdamWeek 8: Effective training in Deep Net- early stopping, Dropout, Batch Normalization, Instance Normalization, Group NormalizationWeek 9: Recent Trends in Deep Learning Architectures, Residual Network, Skip Connection Network, Fully Connected CNN etc.Week 10: Classical Supervised Tasks with Deep Learning, Image Denoising, Semanticd Segmentation, Object Detection etc.Week 11: LSTM NetworksWeek 12: Generative Modeling with DL, Variational Autoencoder, Generative Adversarial Network Revisiting Gradient Descent, Momentum Optimizer, RMSProp, Adam
Taught by
Prof. Prabir Kumar Biswas
Related Courses
-
Deep Learning - IIT Ropar
Indian Institute of Technology, Ropar, NPTEL
-
Introduction to Deep Learning
Higher School of Economics
2.7 -
Introduction to Deep Learning
Purdue University
-
Deep Learning with Python and PyTorch
IBM
-
Deep Learning for Business
Yonsei University
-
Machine Learning with Python: from Linear Models to Deep Learning
Massachusetts Institute of Technology
2.2
Reviews
0.0 rating, based on 0 reviews