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If you are interested in developing algorithms for robotics and autonomous systems using ROS, there is an upcoming livestream just for you.
In this livestream, Jose Avendano Arbelaez and Ronal George will show you how to build and deploy autonomous algorithms using ROS. Using examples, they will show how to interface with ROS networks using publishers and subscribers, build algorithms for mapping, planning and navigation and deploying algorithms as ROS nodes.
Sign up here to get notification when it start streaming at 11:00 am (EDT) on Sep 1 view in your timezone
https://www.youtube.com/watch?v=TDTYFJA3L5w
Congratulations, @Karim for winning the 1st ever Editor's Pick badge awarded for MATLAB Answers, in recoginition of your awesome solution in How to find X and Y coordinates of maximum gap between curves?
This is a new badge we just introduced to recognize awesome answers people contribute and yours was picked for discovering a creative way to solve the problem, and made the solution clear, and reproducible. Thank you so much for setting a high standard for MATLAB Answers and for your ongoing contribution to the community.
MATLAB Central Team
Congratulations, @Matt J for reaching this major milestone!
You provided 9717 answers at the acceptance rate of 75.23% and received 3281 votes. Thank you for your contribution to the community!
MATLAB Central Team
Watch live as Brandon Armstrong and Cris LaPierre import, visualize, and compute statistics without writing code in MATLAB.
The first challenge when starting a new project is importing and exploring the data to determine what it contains. This is especially true if your files contain a mix of numeric, text, and categorical data.
MATLAB has many new tools to simplify this process. Using app-based workflows enable you to spend more time investigating and exploring your data and less time troubleshooting code. Importantly, the code required to repeat your analysis is auto-generated so you can apply the same steps to new files and have others reproduce your work.
Date: 8/25 at 11am EDT - View in your timezone
Link: https://youtu.be/ViI01KNIMh4
Join us on a upcoming live to learn about how the deep learning frameworks in MATLAB and Simulink can be used with TensorFlow and PyTorch to provide enhanced capabilities for building and training your Machine Learning model.
Watch this preview to learn more. https://youtu.be/ZPQgcFPCFZM