Need help with deep-learning?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

udacity
3.6K Stars 4.3K Forks MIT License 349 Commits 91 Opened issues

Description

Repo for the Deep Learning Nanodegree Foundations program.

Services available

!
?

Need anything else?

Contributors list

Deep Learning Nanodegree Foundation

This repository contains material related to Udacity's Deep Learning Nanodegree Foundation program. It consists of a bunch of tutorial notebooks for various deep learning topics. In most cases, the notebooks lead you through implementing models such as convolutional networks, recurrent networks, and GANs. There are other topics covered such as weight intialization and batch normalization.

There are also notebooks used as projects for the Nanodegree program. In the program itself, the projects are reviewed by Udacity experts, but they are available here as well.

Table Of Contents

Tutorials

Projects

  • Your First Neural Network: Implement a neural network in Numpy to predict bike rentals.
  • Image classification: Build a convolutional neural network with TensorFlow to classify CIFAR-10 images.
  • Text Generation: Train a recurrent neural network on scripts from The Simpson's (copyright Fox) to generate new scripts.
  • Machine Translation: Train a sequence to sequence network for English to French translation (on a simple dataset)
  • Face Generation: Use a DCGAN on the CelebA dataset to generate images of novel and realistic human faces.

Dependencies

Each directory has a

requirements.txt
describing the minimal dependencies required to run the notebooks in that directory.

pip

To install these dependencies with pip, you can issue

pip3 install -r requirements.txt
.

Conda Environments

You can find Conda environment files for the Deep Learning program in the

environments
folder. Note that environment files are platform dependent. Versions with
tensorflow-gpu
are labeled in the filename with "GPU".

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.