Skip to content
View AlbertoMarinelli's full-sized avatar
🚀
🚀

Block or report AlbertoMarinelli

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse

Popular repositories Loading

  1. Neural-Network-from-scratch Neural-Network-from-scratch Public

    Neural Network trained through a classical Back-Propagation (BP) approach and employing both the momentum gradient-based optimization technique and L2-regularization implemented from scratch using …

    MATLAB 1 1

  2. QRI-ELM-and-ELM-with-Standard-Momentum QRI-ELM-and-ELM-with-Standard-Momentum Public

    In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) wh…

    MATLAB 1 1

  3. Siamese-Transformer-Networks-for-Key-Point-Analysis Siamese-Transformer-Networks-for-Key-Point-Analysis Public

    The aim of this project is to implement and explore architectures based on Siamese Transformer networks to solve Natural Language Processing tasks, in particular the one proposed by IBM’s shared ta…

    Jupyter Notebook

  4. Ontology-for-italian-research-organisation Ontology-for-italian-research-organisation Public

    Creation of an ontology for an Italian research organisation

  5. ISPR-midterms ISPR-midterms Public

    Assignments for the course of Intelligent Systems for Pattern Recognition (university of Pisa)

    Python

  6. Data-Mining-UniPi Data-Mining-UniPi Public

    Forked from alessandrocubic/Unipi-Data-Mining-project-AY-22-23

    Data Mining project carried out on two datasets extracted from the Twitter platform, one on Users and one on Tweets

    Jupyter Notebook