# introtodeeplearning_labs

**Repository Path**: limbercode/introtodeeplearning_labs

## Basic Information

- **Project Name**: introtodeeplearning_labs
- **Description**: Lab Materials for MIT 6.S191: Introduction to Deep Learning
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-11-09
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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](http://introtodeeplearning.com)! 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](https://colab.research.google.com/), and then select the "GitHub" tab in the pop-up window. Enter the GitHub link to the [6.S191 Repository](https://github.com/aamini/introtodeeplearning_labs/), 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!