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https://github.com/data-science-in-mechanical-engineering/mooc_rl

Repository for the edX course "Reinforcement Learning"

https://github.com/data-science-in-mechanical-engineering/mooc_rl

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic publication links
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    Scientific vocabulary similarity
    Low similarity (12.1%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

Repository for the edX course "Reinforcement Learning"

Basic Info
  • Host: GitHub
  • Owner: Data-Science-in-Mechanical-Engineering
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 4.27 MB
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 3
  • Open Issues: 0
  • Releases: 0
Created almost 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

MOOC Reinforcement Learning Code Base

Welcome to the code base for the MOOC on Reinforcement Learning! Below is an overview of the repository structure, instructions for setting up the environment locally, the binder link, and how to access and use the code.

Repository Structure

The repository is organized into folders by weeks. We provide notebooks for Week 3, Week 5, Week 7, and Week 8.

Getting Startet

There are two possible options for working with the provided notebooks: setting up a local environment on you machine or using Binder. Note that Binder is a free hosting service and therefore training a model will likely be faster on you local machine.

Setting Up the Environment Locally

To run the code and notebooks on your local machine, you'll need to set up a Python environment that includes all the required dependencies. This repository includes an environment.yml file that specifies the necessary packages. Follow the steps below to set up the environment:

  1. Clone the repository:

    bash git clone https://github.com/Data-Science-in-Mechanical-Engineering/mooc_rl.git cd mooc_rl

  2. Create a new conda environment:

    bash conda env create -f environment.yml

  3. Activate the environment:

    bash conda activate MOOC_RL

  4. Launch Jupyter Lab:

    bash jupyter lab

Running the Code on Binder

If you prefer not to install the environment locally, you can easily run the notebooks in a cloud environment using Binder. Simply click the link below to launch the repository in Binder:

Binder

This will open the repository in an interactive Jupyter Notebook environment without needing to set up anything on your local machine.

Contributing

If you find any issues or have suggestions for improvements, feel free to open an issue or submit a pull request. We will not actively manage these but suggestions may improve future iteration of this course.

Happy learning, and good luck with your Reinforcement Learning journey!

Your MOOC RL Team

Owner

  • Name: Data Science in Mechanical Engineering (DSME)
  • Login: Data-Science-in-Mechanical-Engineering
  • Kind: organization
  • Location: Aachen, Germany

Public code repository of the Institute for Data Science in Mechanical Engineering at the RWTH Aachen University

GitHub Events

Total
  • Watch event: 2
  • Fork event: 3
Last Year
  • Watch event: 2
  • Fork event: 3

Dependencies

environment.yml pypi
  • gymnasium ==0.26.3
  • pygame ==2.1.2