In this project we faced a classification problem on a very simple literature dataset, Monk, with the aim of becoming more familiar with **libraries such as Keras, Tensorflow, PyTorch**.

Then the real aim of the project was to find the best configuration of a **neural network for the solution of a regression task with two outputs**.

The project also saw the in-depth application of algorithms such as SVM and KNN, but **focused in particular on neural networks**, which were the main subject of the course.

## Theory in this exam

Many hours were also dedicated to the good application of machine learning, to the** theoretical study of the statistical theory behind the models**.

Advanced topics such as **reservoir computing, recurrent and recursive neural network **were also seen, only at a theoretical level.

## Download of the document

The complete report with all the details of the **grid searches carried out**, the validation techniques carried out, can be downloaded below.