This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

The Java implementation of Dive into Deep Learning (D2L.ai)

A easy tool to download usc den video using just one right click. Using tampermonkey and node.js

Adds a few Quality of Life tweaks to the online educational platform Brightspace Desire2Learn (D2L).

[WIP] Dive into Deep Learning (Vietnamese Version) https://github.com/d2l-ai/d2l-en

An angular application to easily view and save, data-sets retrieved using Brightspace APIs. Using a Go backend

Dive to Deep Learning with Pytorch C++ API

Sync user accounts to d2l lms

Brightspace/Desire2Learn's Python "D2LValence_Util" package.

Practise colabs of self taught deep learning from #d2l

Using the OAuth 2.0 flow to get data from Brightspace APIs.

Learn from *Dive into Deep Learning*, take notes, and do some modification.

This repo provides Pytorch implementation for codes in the book "Dive Into Deep Learning" (http://d2l.ai/) and course Berkeley STAT 157 (https://courses.d2l.ai), which gives a brief tutorial on deep learning methods.

yasnippet snippets for D2L/Brightspace CSV Question format

IAM-less AWS API access for humans.

Nightwatch test for OCSB students to automate their mandatory daily attendance.

This is a series of R Programs used to randomly generate questions and answers within WMU's D2L E-learning system. Several nice features are included or in production, such as user-friendly function wrappers and clear comments to outline the code. The final results are thousands of multiple-choice questions as D2L-compatible CSV and JPG files.

Dive Into Deep Learning (d2l.ai), Using Jax & DeepMind's dm-haiku