Mit Deep Learning
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Tensorflow Examples | 42,312 | 7 months ago | 218 | other | Jupyter Notebook | |||||
| TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) | ||||||||||
| 100 Days Of Ml Code | 40,344 | 3 months ago | 61 | mit | ||||||
| 100 Days of ML Coding | ||||||||||
| 100 Days Of Ml Code | 19,753 | a year ago | 9 | mit | Jupyter Notebook | |||||
| 100-Days-Of-ML-Code中文版 | ||||||||||
| Recommenders | 15,739 |  | 2 | 17 days ago | 11 | April 01, 2022 | 159 | mit | Python | |
| Best Practices on Recommendation Systems | ||||||||||
| Awesome Pytorch List | 13,909 | 2 months ago | 3 | |||||||
| A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc. | ||||||||||
| Machine Learning Tutorials | 12,876 | 5 months ago | 33 | cc0-1.0 | ||||||
| machine learning and deep learning tutorials, articles and other resources | ||||||||||
| Stanford Tensorflow Tutorials | 10,248 | 2 years ago | 88 | mit | Python | |||||
| This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research. | ||||||||||
| Mit Deep Learning | 9,328 | 7 months ago | 15 | mit | Jupyter Notebook | |||||
| Tutorials, assignments, and competitions for MIT Deep Learning related courses. | ||||||||||
| Computervision Recipes | 8,950 | 4 months ago | 65 | mit | Jupyter Notebook | |||||
| Best Practices, code samples, and documentation for Computer Vision. | ||||||||||
| Haystack | 8,935 |  | 2 | 8 hours ago | 29 | July 06, 2022 | 356 | apache-2.0 | Python | |
| :mag: Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT and alike). Haystack offers production-ready tools to quickly build complex question answering, semantic search, text generation applications, and more. | ||||||||||
MIT Deep Learning
This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress.
Tutorial: Deep Learning Basics
This tutorial accompanies the lecture on Deep Learning Basics. It presents several concepts in deep learning, demonstrating the first two (feed forward and convolutional neural networks) and providing pointers to tutorials on the others. This is a good place to start.
Links: [ Jupyter Notebook ] [ Google Colab ] [ Blog Post ] [ Lecture Video ]
Tutorial: Driving Scene Segmentation
This tutorial demostrates semantic segmentation with a state-of-the-art model (DeepLab) on a sample video from the MIT Driving Scene Segmentation Dataset.
Links: [ Jupyter Notebook ] [ Google Colab ]
Tutorial: Generative Adversarial Networks (GANs)
This tutorial explores generative adversarial networks (GANs) starting with BigGAN, the state-of-the-art conditional GAN.
Links: [ Jupyter Notebook ] [ Google Colab ]
DeepTraffic Deep Reinforcement Learning Competition
DeepTraffic is a deep reinforcement learning competition. The goal is to create a neural network that drives a vehicle (or multiple vehicles) as fast as possible through dense highway traffic.
Links: [ GitHub ] [ Website ] [ Paper ]
