falcon
Keras
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falcon | Keras | |
---|---|---|
9 | 77 | |
9,384 | 60,937 | |
0.4% | 0.6% | |
6.7 | 9.9 | |
8 days ago | 1 day ago | |
Python | Python | |
Apache License 2.0 | 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.
falcon
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Is something wrong with FastAPI?
Falcon FastAPI Sanic Starlite (disclosure: I do work here)
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A Look on Python Web Performance at the end of 2022
Sanic is very very popular with 16.6k stars, 1.5k forks, opencollective sponsors and a very active github. Falcon is more popular than japronto with 8.9k stars, 898 forks, opencollective sponsors and a very active github too. Despite Japronto been keeped as first place by TechEmPower, Falcon is a way better solution in general with performance similar to fastify an very fast node.js framework that hits 575k requests per second in this benchmark.
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Flask vs FastAPI?
I prefer Falcon for kicking up an API.
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Python for everyone : Mastering Python The Right Way
Falcon
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Pyjion – A Python JIT Compiler
And here's a project that's mostly Python, and optionally uses Cython https://github.com/falconry/falcon
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2 Questions to Ask Before Choosing a Python Framework
To help with the above two cases I would consider using a microframework, and the Python community provides many solutions. In my professional career I’ve had the opportunity to work with three very good alternatives to Django: Flask, Falcon, and Fast API. Flask is designed to be easy to use and extend. It follows the principles of minimalism and gives more control over the app. Choosing it, developers can use multiple types of databases, which is not easy to do in Django. We can also plug in our favorite ORM and use it without any risk of unpredictable app behavior. In contrast to Django, it’s easy to integrate NoSQL databases with Flask.
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Do you know any Python projects on Github that are examples of best practices and good architecture?
This may not be exactly what you asked for but I found contributing to open source projects really exposed me to different approaches I never would have considered and may not have fully grasped had I not had to actually dive into the code to solve an issue. Falcon is a great place to start and the guys are super friendly there.
- Falcon 3.0 released!
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Designing rest APIs as a data engineer
https://falcon.readthedocs.io/en/stable/ https://fastapi.tiangolo.com/
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.
- free categorical predictive analytic software?
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
hug - Embrace the APIs of the future. Hug aims to make developing APIs as simple as possible, but no simpler.
scikit-learn - scikit-learn: machine learning in Python
Dependency Injector - Dependency injection framework for 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
connexion - Connexion is a modern Python web framework that makes spec-first and api-first development easy.
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
apistar - The Web API toolkit. 🛠
tensorflow - An Open Source Machine Learning Framework for Everyone
restless - A lightweight REST miniframework for Python.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.