johnny-five
Keras
johnny-five | Keras | |
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21 | 78 | |
13,201 | 60,937 | |
- | 0.3% | |
1.3 | 9.9 | |
6 months ago | 6 days ago | |
JavaScript | Python | |
GNU General Public License v3.0 or later | 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.
johnny-five
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Qwik & Arduino with Johnny Five
Some times ago I have played with johnny-five, a JavaScript Robotics & IoT platform. In short words, we can communicate with our Arduino or Raspberry by using JavaScript with a very friendly syntax.
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Dockerize Javascript IOT Applications
The library Johnny-Five is a Javascript library that allows you to control Arduino and other microcontrollers using Javascript. It is very easy to use and it has a lot of examples that you can use to learn how to use it.
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Is there a differnece if I program the Arduino using NodeJS instead of it language c/c++
+Here is the platform used to program the board http://johnny-five.io/
- Arduino to PC Serial Protocol Library
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From Wi-Fi to Li-Fi, sending data via light using Arduino and JavaScript
I decided to use the Johnny-Five JavaScript framework for this. After installing it , I started by declaring a few variables and instantiating the transmitter board.
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Guide please🙏i will really mean a lot.
IOT is the internet of things. That loosely means - interconnected devices that aren't your standard "computer." You can totally do that with JS and a little computer like an Arduino. You can use https://johnny-five.io/ or something... but I'm talking about - a year from now -
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help - Cannot figure out why I keep getting SyntaxError: Unexpected token {
here it the project's github: https://github.com/rwaldron/johnny-five
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JS Library for controlling devices with cameras
Johnny Five seems like a neat project for that bit. What I'm trying to find is a library for using the camera bit. Sorry if my original question wasn't specific enough. I'll try to clarify here.
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Anybody build / programmed LEDs using Node?
Start here: http://johnny-five.io/
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Firmata on ESP32 (WROOM)
I am trying to put Firmata on ESP32 and connect it to the johnny-five lib (or any other JS client). I managed to put official Firmata and other forks related to ESP32, but it doesn't work (build+upload succeed), but I'm getting "ready" from the device.
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?
cylon.js - JavaScript framework for robotics, drones, and the Internet of Things (IoT)
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
serialport - Access serial ports with JavaScript. Linux, OSX and Windows. Welcome your robotic JavaScript overlords. Better yet, program them!
scikit-learn - scikit-learn: machine learning in Python
onoff - GPIO access and interrupt detection with Node.js
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
node-rpio - Raspberry Pi GPIO library for node.js
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
spi-device - SPI serial bus access with Node.js
tensorflow - An Open Source Machine Learning Framework for Everyone
pigpio - Fast GPIO, PWM, servo control, state change notification and interrupt handling with Node.js on the Raspberry Pi
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.