Deep Learning with PyTorch and Google Cloud Platform

Nanyan "Rosalie" Zhu and Chen "Raphael" Liu, Columbia University

Overview

This tutorial is designed for the course BMEN4460 instructed by Dr. Andrew Laine and Dr. Jia Guo starting from the Spring 2020 semester at Columbia University. Since we are a medical imaging group, this repository will mainly focus on applications in medical imaging.

This repository is still in progress. We will add one new post per week. Please help us improve this repository by leaving your comments or problems you encountered in the "Issues" section.

Sections

• Step 00: Set up Google Cloud Platform (GCP).
• Step 01: Manage anaconda on GCP.
• Step 02: Set up Jupyter Lab.
• Step 03 (optional): Set up a graphical user interface (GUI) on GCP.

Children Repositories.

1. Simple cell segmentation with a single layered perceptron, introduced in Step 02.

Additional resources.

1. Jupyter Notebook Tricks. Quite cool. There are a lot of things that we never heard of.
2. Udacity Online Course. This is not free, and not relevant to the course BMEN4460 at all. It is just a course we looked into personally. We are not paid or anything to advertise this.

Useful links (to be organized).

• Biomedical Image Analysis.

• (Video)Neural Network Programming - Deep Learning with PyTorch.

• (Video)Introduction - Deep Learning and Neural Networks with Python and Pytorch.

• Free Online Open Courses
  IBM course
  Udacity deep learning course (related github) (This is a part of the expensive Udacity course we mentioned before.)

• Other useful githubs
  The incredible pytorch
  Awesome-pytorch-list

Papers.

• A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications.