- Description
- Need Help?
- Important References
- Code of Conduct
- Contributing
- Helpful Resources
- Technical Tools
Inspired by the collaborative culture of research, we hold regular, enhanced study sessions in Vadodara. At these meetings, we summarise prescribed preparatory material and leverage our individual strengths in computer science, mathematics, statistics, mechanical, and robotics to cement our comprehension of concepts and to do robotics research.
Over the course of our sessions, we follow three parallel paths:
- Theory: We study academic textbooks, exercises, and coursework so that we command strong theoretical foundations for mathematical modelling and reinforcement learning. Broadly, we cover calculus, algebra, probability, computer science, with a focus on their intersection at machine learning and deep reinforcement learning.
- Application: We practice exercises in the real world. We typically commence by collectively following tutorials then we move on to solving novel and illustrative data problems involving a broad range of techniques.
- Presentations: Study group members regularly share their progress on projects and their area of expertise. This elicits novel discourse outside of the relatively formal paths 1 and 2, playfully encouraging along serendipity.
Need help? Found an issue? Have a feature request? Checkout our support page
- Lab exercises: https://github.com/ELSPL/RoboticsStudyGroup/tree/master/Labs
- Lab related material: https://github.com/ELSPL/RoboticsStudyGroup/tree/master/Docs
- Wiki: https://github.com/ELSPL/RoboticsStudyGroup/wiki
- Issue tracker: https://github.com/ELSPL/RoboticsStudyGroup/issues
- Slack chat room:
We want everyone to feel welcome to contribute to our study group and participate in discussions. In that spirit please have a look at our code of conduct
We have provided an extensive guidelines for beginners and those contributing, which includes:
- Workflows for beginners
- Guidelines
- Issue Reporting
- Coding Standards, Style and Convention
- Pull Request Workflow with git and github
For more information, please read the see the contributing guide