We have used huge amount of online resources for this course. All of them are the sole copyright holders of their material. Here we have refernced them with proper credits.
All the TA's along with the crediting students helped alot to organize and structure this course.
|Sr. No|| |
|1||Basics of Machine Learning: Linear Regression|| || |
|2||Basics of Machine Learning: Linear Classification|| || |
|3||The Intuition of Neural Networks|| || |
|4||Fully Connected Layer and Back Propagation|| || |
|5||Image Classification, Loss Functions, and Optimization|| || |
|6||Computational Graphs|| || |
|7||Activation Functions in Neural Networks|| || |
|8||Initializations in Neural Networks|| || |
|9||Backpropagation and Neural Networks|| || |
|10||Convolutional Neural Networks|| || |
|11||Object Localization and Detection|| || |
|12||Single Shot Multi Box Detector (SSD)|| |
|13||Variational Autoencoder|| || |