FastAPI VS Keras

FastAPI Reviews

Keras Reviews

FastAPI mentions (235)

• Github Sponsor Sebastián Ramírez Python programmer

  He is probably most well know for creating FastAPI that I taught to some of my clients and Typer that I've never used. - Source: dev.to / 5 days ago

• Python: A SQLAlchemy Wrapper Component That Works With Both Flask and FastAPI Frameworks

  It has been an interesting exercise developing this wrapper component. The fact that it seamlessly integrates with the FastAPI framework is just a bonus for me; I didn't plan for it since I hadn't learned FastAPI at the time. I hope you find this post useful. Thank you for reading, and stay safe as always. - Source: dev.to / 7 days ago

• Building an Email Assistant Application with Burr

  In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it. - Source: dev.to / 14 days ago

• Ask HN: What is your go-to stack for the web?

  For pure APIs: pyapi-server [0]. For classic Web sites: Starlette [1], with SQLAlchemy Core [2] for database integration. Or, if you prefer something with more batteries included, FastAPI [3]. [0] https://pyapi-server.readthedocs.io [1] https://www.starlette.io/ [2] https://docs.sqlalchemy.org/en/20/ [3] https://fastapi.tiangolo.com/. - Source: Hacker News / 3 months ago

• Fun with Avatars: Crafting the core engine | Part. 1

  We will create our API using FastAPI, a modern high-performance web framework for building fast APIs with Python. It is designed to be easy to use, efficient, and highly scalable. Some key features of FastAPI include:. - Source: dev.to / 4 months ago

Keras mentions (31)

• 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. - Source: dev.to / 16 days ago

• 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. - Source: dev.to / 25 days ago

• 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. - Source: dev.to / 11 months ago

• 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. Source: about 1 year ago

• How to query pandas DataFrames with SQL

  Pandas comes with many complex tabular data operations. And, since it exists in a Python environment, it can be coupled with lots of other powerful libraries, such as Requests (for connecting to other APIs), Matplotlib (for plotting data), Keras (for training machine learning models), and many more. - Source: dev.to / over 1 year ago