Python-docker
Keras
Python-docker | Keras | |
---|---|---|
17 | 78 | |
2,466 | 60,972 | |
0.9% | 0.3% | |
8.3 | 9.9 | |
27 days ago | 5 days ago | |
Shell | Python | |
MIT 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.
Python-docker
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Containers Demystified 🐳🤔
This defines which image to inherit from, In this case we are using a Python image with the Python 3.11 version running on a slim version of the Bookwork version of Debian linux. Image definitions can be viewed from the DockerHub TAG link such as the python:3.11-slim-bookworm and official images like this one typically have pretty complicated definitions in order to get them highly optimized.
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Ask HN: Why is there no major push towards Android for Servers and Desktops?
> You are going to eventually run into the same issue most people trying to use Alpine Linux just because of simplicity and being lightweight run: musl is not a completely ABI-compatible seamless replacement to glibc and might cause issue with statically linked binaries, and other annoying issues you won't foresee.
Well, if all you need is the server to run Docker/Podman, SSH and some other limited amount of packages, it shouldn't be too bad. Of course, there are also horror stories of Alpine resulting in way worse performance in select use cases: https://github.com/docker-library/python/issues/509 and there's the fact that Alpine might be popular inside of containers, but way less so outside.
Also, because of the short EOL cycle, I personally ditched Debian on servers (and Alpine in containers) myself for Ubuntu everywhere: https://blog.kronis.dev/articles/using-ubuntu-as-the-base-fo... A bit of a polarizing move (though RPM distros aren't much better at the moment), but it seems to have worked out for me in the end.
Doesn't mean that someone can't try, though, maybe their use case is suitable for Alpine.
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What is the point of intermediate CMD layers in Docker images?
This is the actual raw Dockerfile: https://github.com/docker-library/python/blob/master/3.9/slim-bullseye/Dockerfile
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Imaging ADO build agent with python dependencies installed
I usually cannibalize Docker Community's examples: Here
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Why does the official Docker image of Python not create a user but the node one does?
Official Docker image of Python 3.10.5-slim
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Installing python inside docker container
If you want Python v3.7, perhaps try FROM python:3.7 (link)
- Latest Python 3.9/3.8 images break encoding
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Installing Python3 in Linux
Navigate into the Python directory and configure and ensure enable-optimization option is added as shown in the command below.
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I can't run pip for the docker build
It looks like you are running into this bug: https://github.com/docker-library/python/issues/674
- We don't have any control over the signing process of Docker images we publish
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?
setuptools - Official project repository for the Setuptools build system
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
WhatsApp-Scraping - Python script to get WhatsApp iformation frrom WhatsApp Web
scikit-learn - scikit-learn: machine learning in Python
pymodbus - A full modbus protocol written in python
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
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
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
FFXIV-Craft - An FFXIV Queue Crafting System/manager
tensorflow - An Open Source Machine Learning Framework for Everyone
ismrmrd-python - Python API for the ISMRMRD file format
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.