Initiative by IvLabs to share field-wise learning resources. Here you will find all the courses and online materials which are being followed by IvLabs members. These resources have been carefully handpicked to provide the best knowledge. If you like the repo, please star. This motivates us to update the repo frequently.

Please click on following link to see the more info about the specific topic

• Computer Vision
• Control Theory
• Deep Learning
• Embedded Systems
• Internet of Things-IoT
• Mathematics
• Motion Planning
• Programming Languages
• Quantum Mechanics
• Reinforcement Learning
• State Estimation, Localization and SLAM

To keep yourself updated with the field we highly recommend you listen to Podcasts, read subreddit (eg r/MachineLearning), follow Professors on Twitter, go through proceedings of top conferences. Alongside with doing courses you should also have a good grip with Linux OS and be proficient in programming. Click on following links to see the compilation done by IvLabs members.

• Conferences
• Software Skill building (Linux and GitHub)
• Interesting Reads and Talks

NOTE: Some of the topics are not yet completed. The repo will be updated soon.

1. You are encouraged to add links to the following:
   • Online courses
   • Books
   • Tutorials/Code Implementations
   • Important Research Papers
   • Other useful things
2. All of these should be segregated by sub-topic.
3. Refer to existing sections before contributing a new one.
4. Follow the Fork-Commit-Pull Request cycle for contributing, more on this here. All pull requests should be made for devel branch only.
5. If you create a new topic folder make sure to link that folder in landing page README.md
6. The name of folder should be consistent with exact format of word1-word2. Some NOT allowed forms are word1 word2, word1word2, Word1-word2, etc. This maintains consistency and proper ordering of folder.
7. The topic names in List of Various Fields should be in increasing alphabetical order.