Name: Andrea Favia
Type: User
Company: Aalto University
Bio: ML Engineer.
EIT Digital Master's student in Data
Science.
š Sustainability āļø Health enthusiast š Passionate reader
Location: Zurich, Switzerland
Andrea Favia's Projects
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125
Anomaly Detection with Variational AutoEncoder in TensorFlow for Deep Learning course @TU Eindhoven
Telegram bot to use ChatGPT with vocal commands
Build and analyzed models to classify audio into speech, music, nature sounds etc from Google Dataset AudioSet
Managing family's B&B
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Analysis of first data about the coronavirus for the Italian and Dutch situation for FruitPunch.AI association
keras implementation of conditional random field
Config files for my GitHub profile.
A simple Python wrapper to profile both memory and time of python scripts in Linux or MacOS. Built with Typer š
Blind Geometric Distortion Correction on Images Through Deep Learning
This is a simple script that can be used to infer the google place_id from an address
Implementation & Analysis of KNN classifier on MNIST dataset.
Exercises from Machine Learning course by Andrew Ng
During the Data Mining course @TU Eindhoven I had to implement a MLP from scratch to perform a binary classification problem.
Read one-dimensional barcodes and QR codes from Python 2 and 3.
Volume rendering of MRI images based on Raycasting in Python for the Visualisation course @TU Eindhoven
Python scraping tool to download material developed during my Bachelor's program @Politecnico di Torino
Visualization project @TU Eindhoven with Tableau to gain more insights about the Erasmus+ program.
Web visualization and simple analysis of apps data from the Play store for Viz Course @Politecnico di Torino
YAKET: YAML Keras Trainer (or Yet Another Keras Trainer) is a simple and lightweight trainer module to help you quickly develop Keras models by defining parameters directly from a YAML file.