Turns Data and AI algorithms into production-ready web applications in no time.
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Updated
Jul 3, 2024 - Python
Turns Data and AI algorithms into production-ready web applications in no time.
🧙 Build, run, and manage data pipelines for integrating and transforming data.
ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
Elyra extends JupyterLab with an AI centric approach.
Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Azure DevOps Extension for Azure CLI
pypyr task-runner cli & api for automation pipelines. Automate anything by combining commands, different scripts in different languages & applications into one pipeline process.
A C-like hardware description language (HDL) adding high level synthesis(HLS)-like automatic pipelining as a language construct/compiler feature.
Train and run Pytorch models on Apache Spark.
TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.
The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.
Toloka-Kit is a Python library for working with Toloka API.
Machine Learning eXchange (MLX). Data and AI Assets Catalog and Execution Engine
A library for composing end-to-end tunable machine learning pipelines.
Data pipelines from re-usable components
Service for quick deploying and using dockerized Computer Vision models
Collective Knowledge components for TensorFlow (code, data sets, models, packages, workflows):
Vent is a light-weight platform built to automate network collection and analysis pipelines using a flexible set of popular open source tools and technologies. Vent is python-based, extensible, leverages docker containers, and provides both an API and CLI.
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