Duration : 9 months* (I did for 1.2 years)
Syllabus : Details
Contents
Session 1 - Introduction to Computer Vision - Assignment
Session 2 - Neural Architecture - Assignment
Session 3 - First Neural Network - Assignment
Session 4 - Architecture Basics - Assignment
Session 5 -bBatch normalization and Regularization - Assignment
Session 6 - Advanced Convolutions - Assignment
Session 7 -Network Architectures and Receptive Fields Assignment
Session 8 - Assignment
Session 9 - Data Augumentation - Assignment
Session 10 - Interpretability - Assignment
Session 11 - Advanced Concepts in Training and Learning Rates Assignment
Session 12 - Super Convergenece - Assignment
Session 13 - RESNETS -Assignment
Session 14 - RESNET PART2-Assignment
Session 15 - DENSENETs - Assignment
Session 16 - Object Localization - YOLO
Session 17 - RCNN - Faster RCNN & Mask RCNN
Session 18 - Face Recognition
Session 19 - GENERATIVE ADVERSARIAL NETWORKS Assignment
Session 1 - Neural Word Embeddings -Assignment
Session 2 - Recurrent neural Networks
Session 3 - LSTMs
Session 4 - GRU,Attention mechanism and memory networks
Session 5 - Reinforcement Learning - Assignment
Session 6 - Q Learning
Session 7 - Deep Q learning
Session 8 - Continous Action Spaces- Assignment
Session 9 - A3C and T3D - Assignment
Session 10 - END GAME
Final Project - Project ENDGAME Self Driving Car - TD3