Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Experiment tracking, model registries, feature stores, workflow schedulers and deployment tooling.
Signals: mlops, machine-learning-operations, experiment-tracking, model-registry, feature-store, ml-platform, kubeflow, mlflow
202 results
Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS
Notes on Machine Learning on edge for embedded/sensor/IoT uses
Automation framework for machine learning, forecasting, model evaluation, and interpretation.
A machine learning library for Max and Pure Data
Julia package for kernel functions for machine learning
Simple UI tool to build custom machine learning models.
Machine Learning repository for MQL5
machine learning system examples
Machine Learning In Production (MLOps)
Web-interface + rest API for classification and regression (https://jeff1evesque.github.io/machine-learning.docs)
MLEvolve is an open-source autonomous system for end-to-end machine learning algorithm design and optimization powered by progressive search and experience-driven memory.
LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
Here lies the resources and topics necessary for the role of Data Scientist and Machine Learning
deployKF builds machine learning platforms on Kubernetes. We combine the best of Kubeflow, Airflow†, and MLflow† into a complete platform.
A framework to monitor and improve the performance of PostgreSQL using Machine Learning methods.
Next Generation Experimental Tracking for Machine Learning Operations
Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
🧰 Multi-user development platform for machine learning teams. Simple to setup within minutes.
FeatHub - A stream-batch unified feature store for real-time machine learning
Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng
SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.
Workshop content for applying DevOps practices to Machine Learning workloads using Amazon SageMaker
Mathematica implementations of machine learning algorithms used for prediction and personalization.
Azure Machine Learning for Visual Studio Code, previously called Visual Studio Code Tools for AI, is an extension to easily build, train, and deploy machine learning models to the cloud or the edge with Azure Machine Learning service.
24,523 repositories in the index in total.
