PyTorch Journey

I am writing this during my review multi-step review of PyTorch where I am mostly using Deep Learning with PyTorch and also exploring other educational materials for PyTorch too.

You can find the latest revisions for each step of this work / journey in my Git Repo on DagsHub.

I highly recommend Deep Learning with PyTorch. It is amazingly well written and well organized. While it is not my only source for reviewing PyTorch, it is my central source.

Exploring Pretrained Models And How To Use Them

1_AlexNet Directory

In this directory, I explore using a pretrained model of AlexNet.

AlexNet IS the Winner of the 2012 ImageNet Large Scale Visual Recognition Challenge (ILSVRC)

2_ResNet Directory

In this directory, I explore using a pretrained model of ResNet.

ResNet IS the Winner of the 2015 ImageNet Large Scale Visual Recognition Challenge (ILSVRC)

3_HorseToZebraGAN Directory

In this directory, we explore the use of a CNN that was trained in a GAN architecture.

4_NeuralTalk2 Directory

This is a CNN trained in conjunction with an RNN architecture to describe objects in images.

Tensor Talks

5_Tensors Directory

Since tensors are the fundamental data structure in PyTorch, it makes sense to review their nature and learn to understand them as thoroughly as possible.