H2O is an Open Source Fast Scalable Machine Learning Platform that can used for many tasks (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...).
What's the difference between this Python project and similar ones?
in-memory platform for distributed, scalable machine learning
works seamlessly with big data technologies like Hadoop and Apache Spark
Models' export in MOJO and POJO
Many interfaces like R, Python, Scala, Java, JSON and the Flow notebook/web interface
Anyone who agrees with this pull request could vote for it by adding a 👍 to it, and usually, the maintainer will merge it when votes reach 20.
🔄 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/1090
**Author:** [@fzapfack](https://github.com/fzapfack)
**Created:** 7/5/2018
**Status:** ✅ Merged
**Merged:** 7/5/2018
**Merged by:** [@vinta](https://github.com/vinta)
**Base:** `master` ← **Head:** `patch-1`
---
### 📝 Commits (1)
- [`42c7226`](https://github.com/vinta/awesome-python/commit/42c722648897284bc6d61cf9c6496c3405b6318e) add H2O to machine learning section
### 📊 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?
[H2O](https://github.com/h2oai/h2o-3) is an Open Source Fast Scalable Machine Learning Platform that can used for many tasks (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...).
## What's the difference between this Python project and similar ones?
- in-memory platform for distributed, scalable machine learning
- works seamlessly with big data technologies like Hadoop and Apache Spark
- Models' export in MOJO and POJO
- Many interfaces like R, Python, Scala, Java, JSON and the Flow notebook/web interface
Anyone who agrees with this pull request could vote for it by adding a :+1: to it, and usually, the maintainer will merge it when votes reach **20**.
---
<sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.
📋 Pull Request Information
Original PR: https://github.com/vinta/awesome-python/pull/1090
Author: @fzapfack
Created: 7/5/2018
Status: ✅ Merged
Merged: 7/5/2018
Merged by: @vinta
Base:
master← Head:patch-1📝 Commits (1)
42c7226add H2O to machine learning section📊 Changes
1 file changed (+1 additions, -0 deletions)
View changed files
📝
README.md(+1 -0)📄 Description
What is this Python project?
H2O is an Open Source Fast Scalable Machine Learning Platform that can used for many tasks (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...).
What's the difference between this Python project and similar ones?
Anyone who agrees with this pull request could vote for it by adding a 👍 to it, and usually, the maintainer will merge it when votes reach 20.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.