A modular active learning framework for Python
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Updated
Feb 26, 2024 - Python
A modular active learning framework for Python
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.
Composable GAN framework with api and user interface
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.
Scala Library/REPL for Machine Learning Research
Coq Protocol Playground with Se(xp)rialization of Internal Structures.
Public tutorials and code that accompanies articles
🤖 An automated machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers). Python 3.6 required.
A tool for supervised Machine Learning in OWL and Description Logics
API for the plant disease recognition artificial inteligence project which I collaborated on as a member of Team fort in the NaijaHacks hackaton.
Examples how MLJAR can be used
Simple Machine Learning Web API Example with Falcon
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.
A package for time series data processing, classification, clustering, and prediction.
A repository providing demo code for deploying a lightweight Scikit-Learn based ML pipeline modelling heart disease data as a Google Cloud Function.
A Flask API to deploy machine learning models
A collection of awesome Machine Learning software, libraries, Learning Tutorials, documents, books, resources and interesting stuff in ML
A simple python wrapper over MLJAR API.
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.
R wrapper for MLJAR API
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