gds_env VS reinforcement_learning_course_materials

Compare gds_env vs reinforcement_learning_course_materials and see what are their differences.

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gds_env reinforcement_learning_course_materials
1 1
126 905
- 0.8%
7.8 8.3
20 days ago 18 days ago
Jupyter Notebook Jupyter Notebook
BSD 3-clause "New" or "Revised" License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

gds_env

Posts with mentions or reviews of gds_env. We have used some of these posts to build our list of alternatives and similar projects.

reinforcement_learning_course_materials

Posts with mentions or reviews of reinforcement_learning_course_materials. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing gds_env and reinforcement_learning_course_materials you can also consider the following projects:

AMAYARA-Lab - The アマヤラ Lab project provides a ready-to-use Jupyter Lab environment to help out with Android malware analysis using YARA rules.

ML-Prediction-LoL - In this project I implemented two machine learning algorithms to predicts the outcome of a League of Legends game.