Deep Learning course homeworks

This repo contains my submitted and evaluated homeworks for the Deep Learning course at UniPD - DEI 2021/22.

Homework 1 - From Perceptron to DNN

Implementation of the backpropagation algorithm of the perceptron and a two-layer network, with sigmoid and mean squared error.

Training for the handwritten digits dataset (MNIST dataset) using softmax and cross entropy loss function.

Notebook: HW1

Homework 2 - Optimize and Train Deep Models

Text classification with Tensorflow and Keras on the AG News Subset, dealing with overfitting.

Regularization methods as L1-norm, L2-norm, early stopping. Tuning of hyper-parameters using model selection and Grid Search.

Notebook: HW2

Homework 3 - Convolutional Neural Networks

Development of a simple Convolutional Neural Network for image classification on the CIFAR-10 dataset.

Use of Tensorflow and Keras for hyper-parameters selection to obtain better models.

Notebook: HW3

Homework 4 - Recurrent Neural Networks & Transformer

Development of simples Recurrent Neural Networks for sentiment analysis using the IMDB dataset.

Introduction and testing of the Transformer model and its parameters.

Notebook: HW4

Homework 5 - Autoencoders

Comparison between Single Value Decomposition and different types of Autoencoders on CIFAR-10 dataset.

Linear and non-Linear Autoencoders for sequences with the IMDB dataset.

Notebook: HW5

Homework 6 - Variational Autoencoders

Development of Variational Autoencoders with the MNIST Dataset.

Ad-Hoc layer and custom training step exploration.

Notebook: HW6