ML/DL dataset collection utilities
-
Updated
Dec 17, 2024 - Python
ML/DL dataset collection utilities
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
The official code of "CSTA: CNN-based Spatiotemporal Attention for Video Summarization"
This is the repository that cover all the thing related to machine learning that i covered . This repository is bascially a collection from a lot of resouce and any person using this can have a clear idea about machine learning . I have covered all the type of mahcine learning supervised , unsupervised ,etc .
The Python library of the Khiops AutoML suite
Comprehensive collection of machine learning algorithms covering Supervised and Unsupervised Learning, Artificial Neural Networks, Genetic Algorithms, Bayesian Learning, Fuzzy Logic, and Optimization Techniques. Ideal for beginners and enthusiasts!
MLPro - The Integrative Middleware Framework for Standardized Machine Learning in Python
🚤 Label data at scale. Fun and precision included.
The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
A simple way to synthesize LLM training data. (under construction⚠)
A gymnasium-compatible framework to create reinforcement learning (RL) environment for solving the optimal power flow (OPF) problem. Contains five OPF benchmark environments for comparable research.
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
Toolbox of models, callbacks, and datasets for AI/ML researchers.
Smarter Manual Annotation for Resource-constrained collection of Training data
For our PAI course project, we are building several disease prediction systems, including heart disease, diabetes, Parkinson's, and breast cancer classification. Using machine learning algorithms, we aim to analyze patient data and improve the accuracy of early diagnosis, providing valuable insights to healthcare professionals.
Statistical optimization for AI and machine learning
Two simple AI chatbot that can book hotel rooms for customers or take restaurant orders and can save them on mySQL database.
RAISING: Automated deep learning framework
This project aims to predict the housing prices in Boston using various machine learning techniques, including linear regression, decision trees, and random forests. The data pipeline is designed to handle data ingestion, preprocessing, normalization, splitting into training and testing sets, and model evaluation.
Improving drug safety prediction using Explainable AI
Add a description, image, and links to the supervised-learning topic page so that developers can more easily learn about it.
To associate your repository with the supervised-learning topic, visit your repo's landing page and select "manage topics."