regunathanr/pytorch_tutorial

A series of notebooks from our pytorch tutorial series

Learning Pytorch

Eastbay ML will be hosting a series of meetups as we learn pytorch together. Presenters will be volunteers from the group and are not domain experts but will lead the discussion as we learn together. The meetups assume familiarity with python and some exposure to deep learning concepts.

Eastbay ML Pytorch series - guidelines

• Suitable both to people new to deep learning and people with experience on other frameworks
• Use colab notebooks for hands on learning
• Notebooks should be precanned, but exercises require some coding in class
• Attendees should not require work outside of the meetup
• Sessions recorded, or alternate videos for people that miss a meetup
• Volunteer presenters guide each topic
• Use existing content where available. Presenters are not expected to be authors
• Presenters are not expected to spend more that a couple hours in preparation

Learning Pytorch - Syllabus

Week	Topic	Presenter	Notebook
1/30	Intro,Tensors, GPU,Autograd, nn-model, SGD	Roger	lesson 1
2/13	Torchvision,CNN image classification, Resnet,	Roger
2/27	Data Utilities; Optimizers - Adam, Regularization	Shalom
3/12	visualization and tensorboard	Jerry
3/26	CNN object detection	Praveen
4/9	transfer learning	Selly
4/23	RNNs and time series	Dev
5/7	NLP	Dev
5/21	Parallel and Distributed Training	Jeremy
6/4	Mobile/embedded Platform - Quantization, computational efficiency and deploy to edge	Selly
6/18	RL	Selly
7/2	ACKTR	Roger
7/16	GAN / VAE	Shalom
7/30	Nextgen CNN - Mobilnet, EfficientNet,	Patrick

A series of notebooks from our pytorch tutorial series