TensorRec is a Python recommendation system that allows you to quickly develop recommendation algorithms and customize them using TensorFlow. TensorRec lets you to customize your recommendation system's embedding functions and loss functions while TensorRec handles the data manipulation, scoring, and ranking to generate recommendations.
What's the difference between this Python project and similar ones?
TensorRec gives you a level of customization that other recommendation systems do not. TensorRec allows you to build your own representation functions, which can be anything from simple linear transforms to deep neural networks, and use them to generate recommendations simply within the framework.
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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/969
**Author:** [@jfkirk](https://github.com/jfkirk)
**Created:** 10/30/2017
**Status:** ✅ Merged
**Merged:** 10/31/2017
**Merged by:** [@vinta](https://github.com/vinta)
**Base:** `master` ← **Head:** `patch-1`
---
### 📝 Commits (1)
- [`f60dea2`](https://github.com/vinta/awesome-python/commit/f60dea2e8e9819bc23775e83b9ad13344738e63f) Adds TensorRec
### 📊 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?
TensorRec is a Python recommendation system that allows you to quickly develop recommendation algorithms and customize them using TensorFlow. TensorRec lets you to customize your recommendation system's embedding functions and loss functions while TensorRec handles the data manipulation, scoring, and ranking to generate recommendations.
You can read a blog post I wrote about the project here: https://medium.com/@jameskirk1/tensorrec-a-recommendation-engine-framework-in-tensorflow-d85e4f0874e8
## What's the difference between this Python project and similar ones?
TensorRec gives you a level of customization that other recommendation systems do not. TensorRec allows you to build your own representation functions, which can be anything from simple linear transforms to deep neural networks, and use them to generate recommendations simply within the framework.
--
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/969
Author: @jfkirk
Created: 10/30/2017
Status: ✅ Merged
Merged: 10/31/2017
Merged by: @vinta
Base:
master← Head:patch-1📝 Commits (1)
f60dea2Adds TensorRec📊 Changes
1 file changed (+1 additions, -0 deletions)
View changed files
📝
README.md(+1 -0)📄 Description
What is this Python project?
TensorRec is a Python recommendation system that allows you to quickly develop recommendation algorithms and customize them using TensorFlow. TensorRec lets you to customize your recommendation system's embedding functions and loss functions while TensorRec handles the data manipulation, scoring, and ranking to generate recommendations.
You can read a blog post I wrote about the project here: https://medium.com/@jameskirk1/tensorrec-a-recommendation-engine-framework-in-tensorflow-d85e4f0874e8
What's the difference between this Python project and similar ones?
TensorRec gives you a level of customization that other recommendation systems do not. TensorRec allows you to build your own representation functions, which can be anything from simple linear transforms to deep neural networks, and use them to generate recommendations simply within the framework.
--
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.