MITDeepLearning/introtodeeplearning

★ 8,783⑂ 0

Lab Materials for MIT 6.S191: Introduction to Deep Learning

About MITDeepLearning/introtodeeplearning

MITDeepLearning/introtodeeplearning is an open-source project on GitHub, mainly written in Jupyter Notebook. Lab Materials for MIT 6.S191: Introduction to Deep Learning It currently holds 8,783 stars and 0 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).

Project Overview

AI Homed tracks it on the AI Image Projects board and on the AI AI Image Projects list.

GitHub Repository Details

Repository MITDeepLearning/introtodeeplearning · default branch - · size 0 KB · watchers 0 · source: GitHub REST API and repository README

README

banner

This repository contains all of the code and software labs for MIT Introduction to Deep Learning! All lecture slides and videos are available on the program website.

Instructions

MIT Introduction to Deep Learning software labs are designed to be completed at your own pace. At the end of each of the labs, there will be instructions on how you can submit your materials as part of the lab competitions. These instructions include what information must be submitted and in what format.

Opening the labs in Google Colaboratory:

The 2026 Introduction to Deep Learning labs will be run in Google's Colaboratory, a Jupyter notebook environment that runs entirely in the cloud, so you don't need to download anything. To run these labs, you must have a Google account.

On this Github repo, navigate to the lab folder you want to run (lab1, lab2, lab3) and open the appropriate python notebook (\*.ipynb). Click the "Run in Colab" link on the top of the lab. That's it!

Running the labs

Now, to run the labs, open the Jupyter notebook on Colab. Navigate to the "Runtime" tab --> "Change runtime type". In the pop-up window, under "Runtime type" select "Python 3", and under "Hardware accelerator" select "GPU". Go through the notebooks and fill in the #TODO cells to get the code to compile for yourself!

MIT Deep Learning package

You might notice that inside the labs we install the mitdeeplearning python package from the Python Package repository:

pip install mitdeeplearning

This package contains convienence functions that we use throughout the course and can be imported like any other Python package.

>>> import mitdeeplearning as mdl

We do this for you in each of the labs, but the package is also open source under the same license so you can also use it outside the class.

Lecture Videos

All lecture videos are available publicly online and linked above! Use and/or modification of lecture slides outside of MIT Introduction to Deep Learning must reference:

© MIT Introduction to Deep Learning
> http://introtodeeplearning.com

License

All code in this repository is copyright 2026 MIT Introduction to Deep Learning. All Rights Reserved.

Licensed under the MIT License. You may not use this file except in compliance with the License. Use and/or modification of this code outside of MIT Introduction to Deep Learning must reference:

© MIT Introduction to Deep Learning
> http://introtodeeplearning.com

GitHub Stars & Activity

8,783Stars
0Forks
0Open issues
Jupyter NotebookLanguage

GitHub Popularity

GitHub stars8,783
Forks0
Open issues0
Primary languageJupyter Notebook
License-
Stars gained today0
Created-
Last pushed-

Trending History

Trending statusnot on today's boards

Related AI Projects

1

microsoft / AI-For-Beginners

Jupyter Notebook★ 68,541⑂ 0
2

AccumulateMore / CV

Jupyter Notebook★ 23,714⑂ 0
3

spmallick / learnopencv

Jupyter Notebook★ 23,152⑂ 0
4

ShusenTang / Dive-into-DL-PyTorch

Jupyter Notebook★ 19,500⑂ 0
5

virgili0 / Virgilio

Jupyter Notebook★ 14,982⑂ 0
6

NVIDIA / DeepLearningExamples

Jupyter Notebook★ 14,843⑂ 0
7

advimman / lama

Jupyter Notebook★ 10,260⑂ 0
8

microsoft / computervision-recipes

Jupyter Notebook★ 9,880⑂ 0

More AI Rankings