Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from structured and unstructured data. Data scientists perform data analysis and preparation, and their findings inform high-level decisions in many organizations.
Learn Julia the hard way!
A community-driven ontology for the representation of environments
Python slim template repository
A Docker-based Data Science cookiecutter (for myself)
Large labelled dataset of real-life gas meter images — Vaste ensemble d'images réelles et étiquetées de compteurs de gaz.
My notes about: A Curious Moon by Rob Conery
Template repository with Cookie Cutter Infrastructure that can be forked for every new Data Science project in your organization. It aims to provide a guideline on how to start your project with a more **robust infrastructure** than just using jupyter notebooks.
A template repository for setting up a reproducible JupyterLab datascience environment
Create commonly used plots in HEP with matplotlib and mplhep
Techniques and tools for data science with Clojure
This repository is a collection of code, documentation, and other resources that support the management and automation of a Data Science project.
[Work In Progress] Server/Cloud-ready FastChat Docker images.
end-to-end data science project for fictional IT Insitute.
Taking on the Kaggle Freesound General-Purpose Audio Tagging Challenge
Learn data collection by putting a couple of things into consideration
Scripts for analyzing Hungarian parliamentary speeches
🥃 The Podcast Recommender (WIP)
Social-behavior fluctuation peak detector within a relativistic exponential environment using data science.
📖 Experiment with various machine learning algorithms on various data sets from the University of California, Irvine (UCI) Machine Learning Repository (http://archive.ics.uci.edu/ml/index.html)
🏆 Best of Data Science, Machine Learning, Statistics, and Software Engineering