pyusb | Keras | |
---|---|---|
4 | 78 | |
2,075 | 60,995 | |
1.9% | 0.4% | |
6.3 | 9.9 | |
13 days ago | 4 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.
pyusb
- What should I do now
- 5% of 666 Python repos had comma typo bugs (inc V8, TensorFlow and PyTorch)
- How do I connect my printer using python?
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How to get the input data of HID device using Python Script?
You can write python code that reads the data the scanner is sending, but it's not super simple getting up to speed on this. It might be best to search on python read usb hid device and start experimenting. The links found on the search lead to pyusb which has a tutorial. The first stumbling block is that the tutorial requires data about the device, such as idVendor and idProduct. You can write python code to find these values for your scanner if you don't know them, but you'll have to search on that.
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?
WireViz - Easily document cables and wiring harnesses.
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
LsUSB - Collect lsusb reports and find most popular USB devices
scikit-learn - scikit-learn: machine learning in Python
keyboard - Hook and simulate global keyboard events on Windows and Linux.
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
RaspberryPi-Joystick - A virtual HID USB joystick created using Raspberry Pi
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
pclk-mn10 - (Attempting to) control the PCLK-MN10 USB device
tensorflow - An Open Source Machine Learning Framework for Everyone
akbl - Control the lights of Alienware computers under GNU/Linux systems.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.