Discover @jdestefani Open Source projects

Jacopo De Stefani (@jdestefani)

jdestefani

Stars
54
Global Rank 323,221 (Top 12 %)
Followers 49
Following 42
Registered about 11 years ago
Most used languages

R
33.3 %

Jupyter Notebook
26.7 %

Python
13.3 %

C++
6.7 %

Shell
6.7 %

Dockerfile
6.7 %

JavaScript
6.7 %
Location 🇧🇪 Belgium
Country Total Rank 1,623
Country Ranking

Jupyter Notebook
54

R
72

Dockerfile
185

Shell
488

C++
780

Python
1,110

JavaScript
2,153

StatisticalFoundationsML_INFOF422

Repository for the Statistical Foundation of Machine Learning class (INFO-F-422).

Jupyter Notebook

StatisticalFoundationsML_INFOF422_1819

Repository for the Statistical Foundation of Machine Learning class (INFO-F-422) - Academic Year 2018-2019

Jupyter Notebook

ulb-infof305

Materiel pour les séances TP du cours INFO-F-305 - Modélisation et Simulation, pour l'année académique 2020-2021.

Jupyter Notebook

github-orgbatclone

Python script to perform the batch clone of all the repositories belonging to a certain assignment

ulb-infof105-docker

Additional files for the Docker container created for the class INFO-F-105

UEMTS

R package implementing Univariate Error Measures for Time Series forecasting

MEMTS

R package implementing Multivariate Error Measures for time series forecasting

acronym-generator

Simple dictionary-based acronym generator written in Python (>=3).

E-DFML-Experiments

Repository containing the code for the experiments in the paper "Factor-based framework for multivariate and multi-step ahead forecasting of large scale time series"

BigDataAnalytics_INFOH515

Material for the Big Data Analytics exercise classes - INFOH515 - Big Data : Distributed Data Management and Scalable Analytics - Université Libre de Bruxelles

Jupyter Notebook

jdestefani.github.io

Personal website

MM4Benchmark

R package implementing the multivariate (multi-univariate) extension of the benchmarks used for the M

tsptw-infoh413

Automatically exported from code.google.com/p/tsptw-infoh413

ExtendedDFML

R package implementing the Extended Dynamic Factor Machine Learner multivariate forecasting method

gpuDL-docker

Relevant files for the docker containing Python and R installation for GPU Deep Learning tests