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NYU DLSP20

NYU Deep Learning Spring 2020

From Atcold·Updated June 11, 2026·View on GitHub·

This notebook repository now has a [companion website](https://atcold.github.io/NYU-DLSP20/), where all the course material can be found in video and textual format. The project is written primarily in Jupyter Notebook, distributed under the Other license, first published in 2018. It has gained significant community traction with 6,808 stars and 2,236 forks on GitHub. Key topics include: deep-learning, jupyter-notebook, neural-nets, pytorch.

Latest release: dlsp19DLSP19
January 30, 2020View Changelog →

NYU Deep Learning Spring 2020 (NYU-DLSP20) Binder

This notebook repository now has a companion website, where all the course material can be found in video and textual format.

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Getting started

To be able to follow the exercises, you are going to need a laptop with Miniconda (a minimal version of Anaconda) and several Python packages installed.
The following instruction would work as is for Mac or Ubuntu Linux users, Windows users would need to install and work in the Git BASH terminal.

Download and install Miniconda

Please go to the Anaconda website.
Download and install the latest Miniconda version for Python $\geq$ 3.7 for your operating system.

bash
wget <http:// link to miniconda> sh <miniconda*.sh>

Check-out the git repository with the exercise

Once Miniconda is ready, checkout the course repository and proceed with setting up the environment:

bash
git clone https://github.com/Atcold/NYU-DLSP20.git

Create isolated Miniconda environment

Change directory (cd) into the course folder, then type:

bash
# cd NYU-DLSP20 conda env create -f environment.yml source activate NYU-DL

Start Jupyter Notebook or JupyterLab

Start from terminal as usual:

bash
jupyter lab

Or, for the classic interface:

bash
jupyter notebook

Notebooks visualisation

Jupyter Notebooks are used throughout these lectures for interactive data exploration and visualisation.

We use dark styles for both GitHub and Jupyter Notebook.
You should try to do the same, or they will look ugly.
JupyterLab has a built-in selectable dark theme, so you only need to install something if you want to use the classic notebook interface.
To see the content appropriately in the classic interface install the following:

Contributors

Showing top 12 contributors by commit count.

View all contributors on GitHub →

This article is auto-generated from Atcold/NYU-DLSP20 via the GitHub API.Last fetched: 6/13/2026