gds_env
A containerised platform for Geographic Data Science (by darribas)
reinforcement_learning_course_materials
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University (by upb-lea)
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.
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.