A modular active learning framework for Python
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Updated
Feb 26, 2024 - Python
A modular active learning framework for Python
Composable GAN framework with api and user interface
CAI NEURAL API - Pascal based deep learning neural network API optimized for AVX, AVX2 and AVX512 instruction sets plus OpenCL capable devices including AMD, Intel and NVIDIA.
Scala Library/REPL for Machine Learning Research
A tool for supervised Machine Learning in OWL and Description Logics
🤖 An automated machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers). Python 3.6 required.
K-CAI NEURAL API - Keras based neural network API that will allow you to create parameter-efficient, memory-efficient, flops-efficient multipath models with new layer types. There are plenty of examples and documentation.
Coq Protocol Playground with Se(xp)rialization of Internal Structures.
A package for time series data processing, classification, clustering, and prediction.
A Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository.
Tornado is an open source Human-in-the-loop machine learning tool. It helps you label your dataset on the fly while training your model through a simple web user interface. It supports all data types: structured, text and image.
Examples how MLJAR can be used
Simple Machine Learning Web API Example with Falcon
A simple python wrapper over MLJAR API.
Public tutorials and code that accompanies articles
API for the plant disease recognition artificial inteligence project which I collaborated on as a member of Team fort in the NaijaHacks hackaton.
Assisting library for the ML4CV tutorial based on scikit-learn.
A Julia interface for training and applying models in machine learning and statistics
Simple API serving for Python ML models
Tutorials on how to engineer Machine Learning projects using Deep Neural Networks with PyTorch and Python
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