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A stream-batch unified feature store for real-time machine learning (By Alibaba)
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What is FeatHub?

It is a feature store that facilitates feature development and deployment to reduce duplication of data engineering efforts, simplify feature management, and facilitate feature development-to-deployment iteration
FeatHub is a tool in the Machine Learning Tools category of a tech stack.
FeatHub is an open source tool with 253 GitHub stars and 37 GitHub forks. Here’s a link to FeatHub's open source repository on GitHub

FeatHub Integrations

FeatHub's Features

  • Define features via table joins with point-in-time correctness
  • Define over window aggregation features
  • Define sliding window aggregation features
  • Define features via built-in functions
  • Define feature via Python UDF

FeatHub Alternatives & Comparisons

What are some alternatives to FeatHub?
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
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