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iusztinpaul/README.md

Paul Iusztin

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Senior Machine Learning Engineer • MLOps • Founder @ Decoding ML ~ Courses and articles about building production-grade ML/AI systems.


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My passion is to:

  • Design and implement production AI/ML systems using MLOps best practices.

  • Teach people about the process.

🔗 More about me at https://pauliusztin.me


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Email: [email protected]


DML Logo

Founder @ Decoding ML

→ A channel for battle-tested content on designing, coding, and deploying production-grade ML & MLOps systems.

Join Decoding ML for free articles and tutorials on production-grade AI, ML and MLOps at:


🎨 Creating content takes me a lot of time. If you enjoyed my work, consider supporting me by buying me a coffee.

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  1. PacktPublishing/LLM-Engineers-Handbook PacktPublishing/LLM-Engineers-Handbook Public

    The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices

    Python 2.2k 376

  2. decodingml/llm-twin-course decodingml/llm-twin-course Public

    🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴

    Python 3.1k 510

  3. decodingml/personalized-recommender-course decodingml/personalized-recommender-course Public

    👕 Open-source course on architecting, building and deploying a real-time personalized recommender for H&M fashion articles.

    Jupyter Notebook 160 34

  4. hands-on-llms hands-on-llms Public archive

    🦖 𝗟𝗲𝗮𝗿𝗻 about 𝗟𝗟𝗠𝘀, 𝗟𝗟𝗠𝗢𝗽𝘀, and 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀 for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

    Jupyter Notebook 3.2k 495

  5. decodingml/articles-code decodingml/articles-code Public

    💻 Decoding ML articles hub: Hands-on articles with code on production-grade ML

    Jupyter Notebook 116 18

  6. energy-forecasting energy-forecasting Public

    🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

    Python 883 198