Based on our record, Python Poetry should be more popular than Keras. It has been mentiond 162 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you’ve been managing Python projects long enough, you’ve probably dealt with a mess of tools: pip, pip-tools, poetry, virtualenv, conda, maybe even pdm. - Source: dev.to / 17 days ago
First, there was pip. Combined with a requirements.txt, it seemed like a great idea – a straightforward method to declare dependencies explicitly. Luckily, we quickly realized this method tends to spiral into chaos, particularly when developers use "tricks" like pip freeze to lock dependencies rigidly. Fortunately, the Python ecosystem has evolved, introducing modern solutions like Poetry and now uv, offering... - Source: dev.to / about 1 month ago
Anyway, enough reminiscing about the past, this is not intended to be the ultimate guide on asynchronous programming, but a more pragmatic quick-start guide I wish I had back then. Assuming we are in a properly managed project (either through tools like poetry or uv), let’s start with a new module telegram.py for our telegram bot. Remember to add python-telegram-bot dependency to the project. - Source: dev.to / about 2 months ago
Managing dependencies in Python projects can often become cumbersome, especially as projects grow in complexity. Poetry is a modern dependency management and packaging tool that simplifies this process, offering a streamlined way to create, manage, and distribute Python projects. - Source: dev.to / 3 months ago
Learn more about poetry here . It’s a great tool. - Source: dev.to / 3 months ago
The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / 5 days ago
If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and running—an essential part of the startup hustle. - Source: dev.to / 6 months ago
At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / 7 months ago
The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 11 months ago
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. - Source: dev.to / about 1 year ago
Conda - Binary package manager with support for environments.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
pip - The PyPA recommended tool for installing Python packages.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
pre-commit by Yelp - A framework for managing and maintaining multi-language pre-commit hooks
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.