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Source channel @githubtrending · Post #14728 · May 20

#typescript#android#appwrite#backend#backend_as_a_service#docker#firebase#flutter#hacktoberfest#hosting#ios#javascript#nextjs#react#react_native#reactnative#self_hosted#selfhosted#serverless#swift#web Appwrite is a backend platform that helps you build web, mobile, and Flutter apps quickly and easily. It handles complex tasks like user authentication, database management, file storage, and more, so you don’t have to build these from scratch. Appwrite is open source, secure, and works with many programming languages and frameworks. You can use it in the cloud or host it yourself using Docker. The main benefit is that it saves you time and effort, letting you focus on creating great features for your app instead of worrying about backend setup and maintenance[3][5][1]. https://github.com/appwrite/appwrite

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Repositorio data science

@repo_science · Post #3807 · 12/19/2023, 05:08 AM

#AutoML 🐍 AutoML: Build Production-Ready Models Quickly! Learn the basics of building production-ready automated machine learning (AutoML) models. ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----

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@githubtrending · Post #14863 · 06/24/2025, 01:30 PM

#other#automl#chatgpt#data_analysis#data_science#data_visualization#data_visualizations#deep_learning#gpt#gpt_3#jax#keras#machine_learning#ml#nlp#python#pytorch#scikit_learn#tensorflow#transformer This is a comprehensive, regularly updated list of 920 top open-source Python machine learning libraries, organized into 34 categories like frameworks, data visualization, NLP, image processing, and more. Each project is ranked by quality using GitHub and package manager metrics, helping you find the best tools for your needs. Popular libraries like TensorFlow, PyTorch, scikit-learn, and Hugging Face transformers are included, along with specialized ones for time series, reinforcement learning, and model interpretability. This resource saves you time by guiding you to high-quality, actively maintained libraries for building, optimizing, and deploying machine learning models efficiently. https://github.com/ml-tooling/best-of-ml-python