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.
A Julia interface for training and applying models in machine learning and statistics
API for the plant disease recognition artificial inteligence project which I collaborated on as a member of Team fort in the NaijaHacks hackaton.
Public tutorials and code that accompanies articles
Assisting library for the ML4CV tutorial based on scikit-learn.
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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