Skip to content
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Jupyter Notebook Python
Branch: master
Clone or download
aamini Merge pull request #35 from ozankaraali/master
Tensorflow version 1.13 to 1.14 (for Google Colab)
Latest commit 05b1239 Jul 23, 2019
Type Name Latest commit message Commit time
Failed to load latest commit information.
lab1 Tensorflow version 1.13 to 1.14 (for Google Colab) Jul 1, 2019
lab2 fixed links Jan 29, 2019
lab3 sizes error Feb 7, 2019
.gitignore complete version without solutions Jan 28, 2018 Update Jan 27, 2019 add scale to plotter Jan 29, 2019

MIT 6.S191: Introduction to Deep Learning

This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available on the course website.

Opening the labs in Google Colaboratory:

The 2019 6.S191 labs will be run in Google's Colaboratory, a Jupyter notebook environment that runs entirely in the cloud, you don't need to download anything. To run these labs, you must have a Google account. You have two options to open these labs in Colab.

Option 1: On this Github repo, navigate to the lab you want to run and open the appropriate python notebook (*.ipynb). Click the "Run in Colab" link on the top of the lab. That's it!

Option 2: Go to Colab, and then select the "GitHub" tab in the pop-up window. Enter the GitHub link to the 6.S191 Repository, and open the relevant lab.

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 2", and under "Hardware accelerator" select "GPU". Go through the notebooks and fill in the #TODO cells to get the code to compile for yourself!

You can’t perform that action at this time.