machine learning

Armadillo: fast C++ library for linear algebra (matrix maths) & scientific computing - https://arma.sourceforge.net

Extract video representations (semantic, geometric, deep features) for the frames of any video.

A landcover classification tool based for humans. Classifier does "traditional" supervised and unsupervised learning. Image segmentation and soon also object detection

Bahn-Vorhersage - The best Train Delay Prediction System.

Statistics for sci-kit learn.

Package for generating and inverse-designing 2D lattice materials. Represents lattices as heterogeneous graphs and utilizes message passing, automatic differentiation and surrogate gradients for the inverse design.

Finally a smart RSS reader which doesn't suck ass or your data.

Instance Hardness analysis in Machine Learning

Benchmarking framework for machine learning with fNIRS

https://doi.org/10.3389/fnrgo.2023.994969

Code de mon blog technique, accessible à l'adresse : https://say-it-with-data-18ca51.gitlab.io/

Webpage for the L52+ lab

Sashimi - study the organisation and evolution of corpora

Data Science / Machine Learning Pipeline component for training and deploying ML models using CI

Welcome to the "AI_Course_Template" - the basic repository template for students enrolled in the Artificial Intelligence course in the Department of Computer Science. This repository is designed to provide a standardized structure and set of guidelines for student projects, facilitating organized development, easy navigation, and consistent documentation.

Key Features:

Structured directory: Includes predefined folders for data (both raw and processed), source code, tests, and documentation, ensuring a clean and organized project workspace.

Comprehensive README Template: A guide to help students effectively document their project overview, goals, installation process, data descriptions, usage instructions, and contribution guidelines.

Resource Hub: Serves as a central location for essential resources, reference materials, and project-specific instructions.

Collaboration Ready: Configured to support collaborative projects, encouraging students to work together efficiently and share their progress.

Purpose:

This template is designed to streamline the project setup process, allowing students to focus more on the innovative aspects of AI and machine learning, rather than the initial setup and organization. By following this template, students will learn the importance of project organization, clear documentation, and consistent coding practices that are essential for any aspiring AI professional.

$ mldev | is a data science experiment automation and reproducibility toolkit.

check our experiment templates: https://gitlab.com/mlrep

Programtervező Informatikus MSc - Képfeldolgozás haladóknak MSc gyak. projektmunka