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Source channel @githubtrending · Post #14745 · May 24
#python#allowlist#blocklist#disposable#domain#email#filter#hacktoberfest#pypi This resource provides a comprehensive, regularly updated list of disposable email domains used to block fake or temporary email addresses that people often use to spam or abuse online services. By using this list, you can prevent users from registering with throwaway emails, improving the quality and security of your user base. It offers easy integration examples in many programming languages, helping you quickly check if an email is disposable and reject it if needed. This keeps your system cleaner, reduces spam, and ensures users provide real, permanent emails for better communication and trust. The list is free to use and open for contributions, making it reliable and community-supported. https://github.com/disposable-email-domains/disposable-email-domains
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@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