This Repository containes codes that I initially used to learn PyTorch
Further it expanded to all the popular Computer Vision applications coded in PyTorch.
It has 3 following Notebooks-
1.) Torch Basics-
a.)Tensor Operations with Pytorch
b.)Exploring basic functions provided by the torch API,Functions from TorchVision API
c.)Linear/Logistic regression with torch
d.)Defining a Linear Neural Net and Classifying MNIST data
e.)Defining a CNN and classifying CIFAR-10 Data.
2.)Torch Advanced-
a.)AutoEncoders on MNIST
b.)Variational AutoEncoders on MNIST
c.)basic GAN on MNIST
d.)Style Transfer
e.)U-NET Detectron2,YOLO etc
3.)Torch Deep Dive-
This a deep dive into Neural Neworks/Image Processing with Pytorch Hooks,Interpretabillity of CNNs,LR Annealing,One cycle Scheduling etc
Additionally there's a notebook by the name Torch_Experiments in which I tinker around with Apps from Pytorch Ecosystem like Ignite and Captum to name a few.
I further plan to try-out TorchText for NLP with torch.
Take a look at Pytorch Official examples here
Feel Free to Fork and Use/Modify