Name: Alessandro Gianfelici
Type: User
Company: MSG Global Solutions
Bio: Lead Data Scientist @ MSG Global Solutions.
My areas of expertize are NLP, CV and time series forecasting.
Passionate about science and technology.
Location: Milan, Italy
Blog: https://www.linkedin.com/in/alessandro-gianfelici/
Alessandro Gianfelici's Projects
A list of awesome NLP resources for Italian language.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Latex source files of my Bachelor's degree thesis.
This is the code I wrote for a challenge organized by an Italian startup.
LaTex CV
A dataset of danish reviews scraped from trustpilot.com, to be used to train sentiment classification models.
Code for Deep-speare: a joint neural model of poetic language, meter and rhyme
Spider to build a car safety dataset from EURONCAP website.
Implementation of the Extended Motif Discovery algorthim for motif discovery in time-series
This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.
Transparent and Efficient Financial Analysis
Tool that tries to guess a person's gender based on their name and location
A simple and user-friendly interface to download data from HYCOM's GLBv0.08 expt_53.X database.
A dataset of italian reviews to train sentiment classification models
Library for fitting the LPPLS model to data.
Suporting analysis for the paper "Finding maneuver motifs in vehicle telematics"
The Latex source file of my Master's degree thesis
A simple script to fund the nearest doctor (medico di base) in the Marche region (Italy)
MlFinlab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
Motiflets
Resources for "Natural Language Processing" Coursera course.
This repo provides the server side code for llmsherpa API to connect. It includes parsers for various file formats.
A personal project about FX exchange forecasting using Oanda's data