e5c54d3 Merge pull request #2 from guillaume-chevalier/master
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📝README.md (+1 -0)
📄 Description
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:
⚡️ 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:
Anyone who agrees with this pull request could submit an Approve review to it.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.
## 📋 Pull Request Information
**Original PR:** https://github.com/vinta/awesome-python/pull/1680
**Author:** [@guillaume-chevalier](https://github.com/guillaume-chevalier)
**Created:** 11/22/2020
**Status:** ❌ Closed
**Base:** `master` ← **Head:** `patch-1`
---
### 📝 Commits (5)
- [`11107d0`](https://github.com/vinta/awesome-python/commit/11107d0009140a48bf4a928d58634c2644b690b5) Add Neuraxle
- [`2a5b5d7`](https://github.com/vinta/awesome-python/commit/2a5b5d72a3762aaea356f0395f8e6ff0523c242e) Update Neuraxle
- [`1e40067`](https://github.com/vinta/awesome-python/commit/1e40067556889f1846943b4409701f99e92fd8c0) Merge pull request #1 from vinta/master
- [`86eb1da`](https://github.com/vinta/awesome-python/commit/86eb1da0268002173604d2dc057477feedc1c1a2) Merge branch 'patch-1' into master
- [`e5c54d3`](https://github.com/vinta/awesome-python/commit/e5c54d3353803dd6272ec3e0c7a20af8a81d8c71) Merge pull request #2 from guillaume-chevalier/master
### 📊 Changes
**1 file changed** (+1 additions, -0 deletions)
<details>
<summary>View changed files</summary>
📝 `README.md` (+1 -0)
</details>
### 📄 Description
## What is this Python project?
[Neuraxle](https://www.neuraxle.org/) is an extension of the Scikit-Learn project to enable more sophisticated Machine Learning projects, as well as Deep Learning projects. Features:
- ⚡️ 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:
- https://www.neuraxle.org/stable/scikit-learn_problems_solutions.html
--
Anyone who agrees with this pull request could submit an *Approve* review to it.
---
<sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
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📋 Pull Request Information
Original PR: https://github.com/vinta/awesome-python/pull/1680
Author: @guillaume-chevalier
Created: 11/22/2020
Status: ❌ Closed
Base:
master← Head:patch-1📝 Commits (5)
11107d0Add Neuraxle2a5b5d7Update Neuraxle1e40067Merge pull request #1 from vinta/master86eb1daMerge branch 'patch-1' into mastere5c54d3Merge pull request #2 from guillaume-chevalier/master📊 Changes
1 file changed (+1 additions, -0 deletions)
View changed files
📝
README.md(+1 -0)📄 Description
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:
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:
--
Anyone who agrees with this pull request could submit an Approve review to it.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.