Pinned Repositories
AI-Against-COVID-19-COSBI
awesome-ai-summerschool
A list of summer schools on Artificial Intelligence, Machine Learning, and Healthcare
awesome-mlss
🤖 Machine Learning Summer School deadlines
Basketball_Men-SQL-and-NoSQL
Bayesian-Rats-Normal-hierarchical-model
Character-Neural-Network
Computer-Scientists-Network
Data-Centers-and-Graphs
Twitter-Elections
Predict Italy's elections using Twitter
Wikipedia-Influenza
guarrasi1995's Repositories
guarrasi1995/Twitter-Elections
Predict Italy's elections using Twitter
guarrasi1995/Wikipedia-Influenza
guarrasi1995/AI-Against-COVID-19-COSBI
guarrasi1995/awesome-ai-summerschool
A list of summer schools on Artificial Intelligence, Machine Learning, and Healthcare
guarrasi1995/awesome-mlss
🤖 Machine Learning Summer School deadlines
guarrasi1995/Basketball_Men-SQL-and-NoSQL
guarrasi1995/Bayesian-Rats-Normal-hierarchical-model
guarrasi1995/Character-Neural-Network
guarrasi1995/Computer-Scientists-Network
guarrasi1995/Data-Centers-and-Graphs
guarrasi1995/DockerToolchain
guarrasi1995/GICS-Clusters
Select a sensible portfolio of stocks, build the data matrix and visualize what’s going on in there. With this data, choose two different association measures, implement the bootstrap procedure described at page 3 and 4 of our notes to build marginal correlation graphs, and compare the results. In particular, visualize the graphs using the gics sectors to annotate/color the nodes, and draw some conclusion: is there any statistical evidence to support the claim that stocks from the same sector cluster together?
guarrasi1995/guarrasi1995.github.io
A beautiful, simple, clean, and responsive Jekyll theme for academics
guarrasi1995/Italian-Referendum
guarrasi1995/Lyrics-Search-Engine
Search engine for songs
guarrasi1995/PhD-School-AI-2024
Jekyll template for a conference website containing program, speaker, talks and room overview
guarrasi1995/recnet
RecNet - Recurrent Neural Network Framework
guarrasi1995/reprodl-fake
guarrasi1995/reprodl2021
Host repository for the "Reproducible Deep Learning" PhD course