🎙️ Who is Paul Iusztin?

Paul Iusztin is a machine learning engineer with over 5 years of experience in the industry with a background in software engineering, and mathematics. He is passionate about building and engineering AI systems using MLOps good practices and active iteration problem-solving processes. Paul have strong experiences working in different machine learning job positions and offers tips and advice for individuals looking to enter the AI field. His mission? To build data-intensive AI/ML systems that innovate the world, as well as his passion for helping other machine learning engineers level up through practical posts, articles, and tutorials. Additionally, Paul published The Full Stack 7-Steps MLOps Framework and MLOps-related topics, including version control with Git and using Airflow for automating machine learning.

💡 In this episode...

Paul discusses building and engineering AI systems using MLOps practices and active iteration problem-solving processes. He also shares his journey through different machine learning job positions and provides tips for entering the AI field. He emphasizes the importance of effective communication with customers and deploying multiple versions of AI/ML projects. Paul talks about the MLOps framework he published, and enhances learning efficiency with ChatGPT. An amazing episode for all MLOps and ML Engineers!

Paul Iusztin: https://www.linkedin.com/in/pauliusztin/
🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: https://github.com/iusztinpaul/energy-forecasting

Thomas Bustos: https://www.linkedin.com/in/thomasbustos/

Artistic Direction & Video: Maxence Kerhoas

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