Created by: guillaume-chevalier
What is this Python project?
Neuraxle is an extension of the Scikit-Learn project to enable more sophisticated Machine Learning projects, as well as Deep Learning projects. Features:
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⚡ ️ Component-Based: Build encapsulated steps, then compose them to build complex pipelines. -
🔥 Evolving State: Each pipeline step can fit, and evolve through the learning process -
🎛 Hyperparameter Tuning: Optimize your pipelines using AutoML, where each pipeline step has their own hyperparameter space. -
🔌 Compatible: Use your favorite machine learning libraries inside and outside Neuraxle pipelines. -
🚀 Production Ready: Pipeline steps can manage how they are saved by themselves, and the lifecycle of the objects allow for train, and test modes. -
🏹 Streaming Pipeline: Transform data in many pipeline steps at the same time in parallel using multiprocessing Queues.
What's the difference between this Python project and similar ones?
This framework is very similar to Scikit-Learn. However, Scikit-Learn has some limitations, and Scikit-Learn users have been stuck with these problems sometimes. Hopefully, Neuraxle solves most of the encountered problems when it comes to using it for deep learning, and is built upon Scikit-Learn with compatibility in mind, rather than as a replacement.
Here is a full article dedicated to the differences between Scikit-Learn and Neuraxle, as well as how Neuraxle solves the problems that Scikit-Learn has:
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