本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Một cuốn sách về Học Sâu đề cập đến nhiều framework phổ biến, được sử dụng trên 300 trường Đại học từ 55 đất nước bao gồm MIT, Stanford, Harvard, và Cambridge.
The Java implementation of Dive into Deep Learning (D2L.ai)
This repository contains Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book.
Dive to Deep Learning with Pytorch C++ API
Adds a few Quality of Life tweaks to the online educational platform Brightspace Desire2Learn (D2L).
A easy tool to download usc den video using just one right click. Using tampermonkey and node.js
ETL data flows in Domo Analytics for querying D2L Brightspace data sets related to awards, rubrics, quizzes, surveys, gradebook and outcomes
Updated content templates (originally designed by D2L Brightspace) with more accessibility and interactivity with flip cards and knowledge checks
Just the flip cards and knowledge checks (multiple choice, short answer, matching, ordering) from d2l-content-templates as standalone HTML pages
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.
Extension to improve the Brightspace/D2L user experience.
Slides for Dive into Deep Learning book
Formats and pivots data from D2L Brightspace intelligent agents, outcomes, and survey reports (manual Excel workflows also included)
An angular application to easily view and save, data-sets retrieved using Brightspace APIs. Using a Go backend
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