Author: Emilio Molina ([email protected])
This repository contains:
- My solutions for the Deep Learning Nanodegree Foundations: https://eu.udacity.com/course/deep-learning-nanodegree-foundation--nd101
- A brief summary of all projects (in this README.md)
A general overview on deep learning, and some hands-on experience with exercises and projects using Tensorflow. I think the content of the nanodegree can be summarized with the 5 delivered projects (and manually reviewed by Udacity).
The solutions can be found in the different folders inside this repository. A brief summary:
In this project you implement your own neural network from scratch using numpy. You implement not only the forward pass (prediction) but also the backpropagation algorithm (training). It is a very simple use case with a single hidden layer, but you obtain very interesting results (see figures).
Very interesting project where you use convolutional neural networks for implementing a image classifier (using CIFAR-10 dataset). Example of the achieved results:
You use a recurrent neural network trained on TV scripts of The Simpsons to automatically generate a new one. This is the kind of script automatically generated:
You use a recurrent neural network to implement a sequence-to-sequence system for language translation. Concretely, you use a dataset of english-to-french translation. Example of translation performed by the system:
This project is quite nice to understand GANs, and at the end of it you have a quite nice convolutional GAN able to generate almost-realistic faces. Check the results:
