This repository contains demo projects and assignment solutions, that I have done during the Udacity Deep Learning Foundation.
Disclaimer: there is probably a code of conduct if you are enrolled in the nanodegree. Copying the code from the repository and pretending it to be sure would be bad. Even looking into it may be an infringement. Talk to your instructor.
The course is just great! You will use and develop neural networks for image recognition with convolution, natural language processing with embeddings and character-based text generation with RNN/LTSM.
- Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Generative Adversarial Networks
I recommend installing the Python bundle Anaconda. All the assignments have been done with Python 3, so download the installation script accordingly. You can then install Jupyter Notebook from conda.
The next step is to install TensorFlow. At the time of writing, the latest release is r1.0, after several upgrades during the course. You can refer to the official documentation and intallation guide. Here is the list of commands:
$ conda create -n tensorflow python=3
$ source activate tensorflow
You can now grab the assignments from here to run my code or the stubs from the TensorFlow repository. All the other prerequisites (like numpy) have to be installed on the fly.
From the repository root, start the Notebook server with jupyter notebook.
All the assignments come from Udacity and the TensorFlow repository