| 21-March-2022 |
1.5 hours |
History of Computer Vision, Top Research in the area, Introduction to Machine Learning, Learning algorithms |
|
|
|
1.5 hours |
Introduction to deep learning, Types of Machine Learning, Problems Classification vs Regression, Linear Regression |
|
|
| 28-March-2022 |
1.5 hours |
What is a Neural Network , House Price Prediction example using Linear Regression, Loss Function |
|
|
|
1.5 hours |
Training a Neural Network, Logistic Regression (Binary Classification), Sigmoid Activation Function, Logistic Regression Cost Function, Log Based Loss Function, Computational Graph |
|
|
| 4-April-2022 |
1.5 hours |
Gradient Descent mathematical derivation, Neural Network with one hidden layer, Computing output of the neural network, |
Assignment 1 |
|
|
1.5 hours |
Vectorization for programming NN, Gradient Descent on 'm' examples, Different Type of activation function in NN |
QUIZ # 1 |
|
| 11-April-2022 |
1.5 hours |
Propagation in Neural Networks, Forward propagation , Backward Propagation |
|
|
|
1.5 hours |
Step by Step example for forward and backward propagation for neural network with one hidden layer (XOR Example) |
|
|
| 18-April-2022 |
1.5 hours |
Neural Network Implementation in python (XOR Example), Techniques for Improving Neural Networks : hyper-parameter Tuning, Dataset Splits |
|
|
|
1.5 hours |
Bias and Variance Trade-off, regularization, dropout Regularization, |
|
|
| 25-April-2022 |
1.5 hours |
Improving Neural Networks, hyperparameters, Dataset splits, Bias and Variance , Mismatched Train/Test Distributions, Data Augmentation Techniques, |
|
|
|
1.5 hours |
Early Stopping Technique, Orthogonalization in Machine Learning, Normalizing Inputs, Vanishing and exploding gradients, |
|
|
| 2-May-2022 |
1.5 hours |
Weight Initialization ,Batch Vs. Mini batch gradient descent, |
Assignment # 2 |
|
|
1.5 hours |
Training with mini-batch Gradient Descent , Multiclass classification |
|
|
| 9-May-2022 |
1 Hour |
Mid Term |
|
|
| 16-May-2022 |
1.5 hours |
SoftMax Function, Training a neural network with softmax function |
|
|
|
1.5 hours |
Edge Detection Examples , Convolutions, Convolutional Masks |
|
|
| 23-May-2022 |
1.5 hours |
Padding ,Strided Convolutions, Convolutions Over Volumes |
|
|
|
1.5 hours |
One Layer of a Convolutional Net, Simple Convolutional Network Example, |
|
|
| 30-May-2022 |
1.5 hours |
Pooling Layers ,CNN Example ,Why Convolution, Why look at case studies |
QUIZ # 3 |
|
|
1.5 hours |
Classic CNN Based Networks, ResNets , Why ResNets Work |
|
|
| 6-June-2022 |
1.5 hours |
Network In Network, Inception Network Motivation , Object Localization |
|
|
|
1.5 hours |
Landmark Detection, Object Detection , Convolutional Implementation Sliding Windows |
Assignment# 2 |
|
| 13-June-2022 |
1.5 hours |
Intersection Over Union, Non-max Suppression, Anchor Boxes |
|
|
|
1.5 hours |
CVPR-RESEARCH ARTICLE -1 (YOLO Algorithm) |
|
|
| 20-June-2022 |
1.5 hours |
What is face recognition, Face Verification, One Shot Learning |
|
|
|
1.5 hours |
Siamese Network, Triplet loss, CVPR-RESEACH PAPER 2 |
QUIZ # 4 |
|
| 27-June-2022 |
1.5 hours |
What is neural style transfer, What are deep CNs learning, Cost Functions |
|
|
|
1.5 hours |
1D and 3D Generalizations, RESEACH PAPER 3 |
|
|
| 4-July-2022 |
1.5 hours |
Group Presentations -1 |
|
|
|
1.5 hours |
Group Presentations-2 |
|
|
| 11-July-2022 |
2 Hour |
Final Term |
|
|
