The Java implementation of Dive into Deep Learning (D2L.ai)
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Updated
May 27, 2024 - Jupyter Notebook
The Java implementation of Dive into Deep Learning (D2L.ai)
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Autosave edits to D2L assignment feedback. A Google Chrome Extension / Plugin
Social Media Monitoring for Twitter in python language
Deep Learning basics in Python using NumPy, PyTorch, and TensorFlow/Keras: linear regression, softmax regression, multilayer perceptron, etc.
Formats and pivots data from Brightspace by D2L intelligent agents, outcomes, and survey reports (manual Excel workflows also included)
Just the flip cards and knowledge checks (multiple choice, short answer, matching, ordering) from d2l-content-templates as standalone HTML pages
Updated content templates (originally designed by Brightspace by D2L) with more accessibility and interactivity with flip cards and knowledge checks
This is an implementation of the "Fast Image Processing with Fully-Convolutional Networks" paper.
Simple Component that adds calliper for measuring lengths in an image
A Flow Launcher plugin for students to quickly open Brightspace D2L course pages and other course content from Flow Launcher
ETL data flows in Domo Analytics for querying Brightspace by D2L data sets related to awards, rubrics, quizzes, surveys, gradebook and outcomes
Study Notes for Dive into Deep Learning using Pytorch. Dive into Deep Learning 中文学习笔记
This my practise code from reading "Dive into Deep Learning" book. Most of the code follows the book's structure but is implemented with slight differences
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.
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