DeepRecommend | 纸上得来终觉浅，绝知此事要躬行

by LongmaoTeamTf Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | DeepRecommend Summary

DeepRecommend is a Python library. DeepRecommend has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

纸上得来终觉浅，绝知此事要躬行

Support

Quality

Security

License

Reuse

Support

DeepRecommend has a low active ecosystem.

It has 30 star(s) with 14 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

DeepRecommend has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of DeepRecommend is current.

Quality

DeepRecommend has 0 bugs and 0 code smells.

Security

DeepRecommend has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

DeepRecommend code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DeepRecommend does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

DeepRecommend releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

DeepRecommend saves you 952 person hours of effort in developing the same functionality from scratch.

It has 2170 lines of code, 171 functions and 35 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

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DeepRecommend Key Features

No Key Features are available at this moment for DeepRecommend.

DeepRecommend Examples and Code Snippets

No Code Snippets are available at this moment for DeepRecommend.

Community Discussions

Trending Discussions on DeepRecommend

I'm facing issues with Data Preparation while using Netflix Data

QUESTION

I'm facing issues with Data Preparation while using Netflix Data

Asked 2021-Jan-27 at 15:47

I'm facing issues with Data Preparation while using Netflix Data. I just cloned a repo from Github and I'm facing issues while trying to run the code in Jupyter Notebook.

...

ANSWER

Answered 2021-Jan-27 at 15:47

I tried this and it worked fine.

Actually, I replaced $NF_PRIZE_DATASET with training_set (this is the folder under the root directory of DeepRecommender folder, training_set contains the dataset which I got from Netflix Dataset) and $NF_DATA with NF_DATA

Source https://stackoverflow.com/questions/65919017

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install DeepRecommend

You can download it from GitHub.
You can use DeepRecommend like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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