Code for my experiments learning deep learning and neuronal networks
Here is a showcase of all most important projects, click the images to show the code:
A RRN using PyTorch (+ a DIY LSTM module) that can predict the origin of a surname:
A neural network that can transfer style to an image, this uses convolutional neuronal networks and is an Udacity's PyTorch exercise.
A neural network that can recognize with ~95% accuracy a letter written in sign language from a photo, created using TensorFlow.
A RRN using PyTorch (using convolutional layers) that classifies images suing the CIFAR10 dataset.
This is a classic example in deep learning, this is a net that recognize digits:
This is a classic exercise, is a simple net that can predict the XOR gate, for this I created myself an nn, and implemented backpropagation for scratch:
