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Hopsworks
- Hopsworks is a data-intensive platform for the design and operation of machine learning pipelines that includes a Feature Store. (Video).
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Kubeflow
- A cloud native platform for machine learning based on Google’s internal machine learning pipelines.
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Open Platform for AI
- Platform that provides complete AI model training and resource management capabilities.
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PyCaret
) - low-code library for training and deploying models (scikit-learn, XGBoost, LightGBM, spaCy)
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Redis-AI
- A Redis module for serving tensors and executing deep learning models. Expect changes in the API and internals.
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Skaffold
- Skaffold is a command line tool that facilitates continuous development for Kubernetes applications. You can iterate on your application source code locally then deploy to local or remote Kubernetes clusters.
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Tensorflow Serving
- High-performant framework to serve Tensorflow models via grpc protocol able to handle 100k requests per second per core
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Seldon
- Open source platform for deploying and monitoring machine learning models in kubernetes - (Video)
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KFServing
- Serverless framework to deploy and monitor machine learning models in Kubernetes - (Video)
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NVIDIA TensorRT Inference Server - TensorRT Inference Server is an inference microservice that lets you serve deep learning models in production while maximizing GPU utilization.
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NVIDIA TensorRT - TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.
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DeepDetect
- Machine Learning production server for TensorFlow, XGBoost and Cafe models written in C++ and maintained by Jolibrain
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MLeap
- Standardisation of pipeline and model serialization for Spark, Tensorflow and sklearn
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BentoML
- BentoML is an open source framework for high performance ML model serving
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Clipper
- Model server project from Berkeley's Rise Rise Lab which includes a standard RESTful API and supports TensorFlow, Scikit-learn and Caffe models
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Cortex