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ROS | Keras | |
---|---|---|
83 | 78 | |
2,626 | 60,937 | |
2.1% | 0.6% | |
2.6 | 9.9 | |
2 months ago | 2 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
ROS
- Google DeepMind's Aloha Unleashed is pushing the boundaries of robot dexterity
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Linux market share passes 4% for first time; macOS dominance declines
I wonder if this could be related to M1/2/3 Macs being worse for x86 system software development than the old Intel Macs. I work on ROS[1] which runs on x86 Linux platforms, but usually develop on a Mac. I may have to move to a Linux laptop soon because there's not an easy path (that I'm aware of) to running x86 ROS code on an M3: compiling the entire system for arm would be a huge headache while running x86 code in a Linux VM under Rosetta has a lot of unknowns.
Obviously my case is a bit of an outlier, but once you add up enough outliers you might see a real impact.
[1] https://www.ros.org
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Getting into Robotics as a Software Engineer
Robotics is a broad field and is a confluence of many specialties: mechanical engineering, hardware engineering, software engineering, control, machine learning, computer vision, anything in between is a good entrance.
Coming from software, if you are interested, I would suggest either:
- Backend platform development (Python, C++ as main programming languages with a strong focus on ROS[1]).
- Frontend development (nothing too different from what's out there).
As small projects I would suggest playing with ROS to learn it and getting a running simulation with a simple robot that you can teleoperate, most of the stack already exists, it's just connecting everything together [2].
Another venue is open source contribution [1] to get known within the community and potentially attract interest from companies. ROS has multiple packages, from cloud infrastructure to drivers and simulation, if you see anything there you could contribute to, they will gladly take contributions.
In general robotics greatly benefits of good technologies from other areas, if there is a tool we use you believe could be better or a lack of good tooling in a specific area, it will get noticed.
So this would be my suggested path: learn C++/Python if you're not familiar with, learn ROS and watch which specialties appear more often in robot related jos posts [3]. If you are really invested, maybe go to a robotics conference as ROSCon to meet other enthusiasts, which companies are engaged with the community, etc.
Good luck!
Note: not everything robot related is done in ROS, but it's almost a standard within the field save for a few exceptions.
[1]: https://www.ros.org/
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How do I start robotics as a teen with no money?
ROS is an operating system designed for robotics (it can be run many different ways) it includes simulations for many robots (including sensors etc) and you can even design your own fully inside the software. https://www.ros.org/
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C++ Project Ideas?
Robotics with ROS https://www.ros.org/ (You can do a lot with simulators and don't require actual HW)
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[Career Advice] Transition from Software Engineer to Robotics
Hardware experience is useful, but not needed to get started working with robotics. With your software background, I recommend you look into learning ROS (Robot Operating System) fundamentals on a personal computer, you can simulate a robot using Gazebo. Good luck!
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Best practices in creating a Rust API for a C++ library? Seeking advice from those who've done it before.
In Robotics, the Open Motion Planning Library (OMPL) is a popular library for multi-dimensional motion planning, and is used by ROS and other robotics-related software. There are no Rust bindings to OMPL (though there is Rust support for software like ROS), and the library is written almost exclusively in C++. There are Python bindings, but those are generated using Py++. The header files throughout OMPL are C++ header files, not C, as they contain namespaces, classes, etc.
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[ANN] NASA's Ogma 1.0.9
[3] https://www.ros.org/
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Newbie to Robotics (Question/Discussion)
ALSO - learn ROS. If you are interested in robotics as a career, this is one of the better things to have good experience for on your resume. There are also good tutorials on using ROS with simulated robots, so if you just want to focus on the software that's a good option :)
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Real-time C++ on Linux
Roboticist here, have you heard of ROS?
Keras
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Library for Machine learning and quantum computing
Keras
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My Favorite DevTools to Build AI/ML Applications!
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development.
- Release: Keras 3.3.0
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Getting Started with Gemma Models
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow.
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Keras 3.0
All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467
You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/
- Keras 3: A new multi-back end Keras
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Can someone explain how keras code gets into the Tensorflow package?
I'm guessing the "real" keras code is coming from the keras repository. Is that a correct assumption? How does that version of Keras get there? If I wanted to write my own activation layer next to ELU, where exactly would I do that?
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How popular are libraries in each technology
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks.
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List of AI-Models
Click to Learn more...
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Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them.
What are some alternatives?
MRPT - :zap: The Mobile Robot Programming Toolkit (MRPT)
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
Robotics Library (RL) - The Robotics Library (RL) is a self-contained C++ library for rigid body kinematics and dynamics, motion planning, and control.
scikit-learn - scikit-learn: machine learning in Python
yarp - YARP - Yet Another Robot Platform
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
DART - DART: Dynamic Animation and Robotics Toolkit
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
PCL - Point Cloud Library (PCL)
tensorflow - An Open Source Machine Learning Framework for Everyone
moveit - :robot: The MoveIt motion planning framework
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.