Ben Xiang Mu Jiang <
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Updated
Oct 14, 2021 - Jupyter Notebook
Ben Xiang Mu Jiang <
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Mot cuon sach ve Hoc Sau de cap den nhieu framework pho bien, duoc su dung tren 300 truong Dai hoc tu 55 dat nuoc bao gom MIT, Stanford, Harvard, va 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.
Updated content templates (originally designed by D2L Brightspace) with more accessibility and interactivity with flip cards and knowledge checks
Dive to Deep Learning with Pytorch C++ API
Adds a few Quality of Life tweaks to the online educational platform Brightspace Desire2Learn (D2L).
Just the flip cards and knowledge checks (multiple choice, short answer, matching, ordering) from d2l-content-templates as standalone HTML pages
ETL data flows in Domo Analytics for querying D2L Brightspace data sets related to awards, rubrics, quizzes, surveys, gradebook and learning outcomes
A easy tool to download usc den video using just one right click. Using tampermonkey and node.js
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.
Jiang <
MCP server for Brightspace (D2L): check grades, due dates, announcements, rosters & more using Claude, ChatGPT, Cursor, or any MCP client. Built with TypeScript and the D2L REST API.
Extension to improve the Brightspace/D2L user experience.
An angular application to easily view and save, data-sets retrieved using Brightspace APIs. Using a Go backend
Formats and pivots data from D2L Brightspace intelligent agents, outcomes, and survey reports (manual Excel workflows also included)
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