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Practical Python Design Patterns for MLOps, LLM Development

Description

Let's briefly look at what practical Python design patterns are, why they are needed, and what they are. We will explain in detail how codes were upgraded in the field through these design patterns. In this process, attendees will understand which codes are bad codes and learn how to upgrade them. In this session, you will gain the power to find and apply design patterns on your own by looking at key cases applied in the field in detail. We will cover each case of machine learning model serving and LLM agent development in depth, and I am sure that you will be able to gain an understanding of MLOps and LLM in addition to design patterns.

Lee Tae-ho Hello, I am Lee Tae-ho, the tech lead at AI startup Korka. Korka is innovating users' online shopping experience with machine learning and LLM. We have been building AdTech capabilities until 2022 and are developing B2B SaaS products while quickly applying LLM in 2023. I have worked in various positions such as backend engineer and machine learning engineer, and am currently working as a tech lead at Korka. In 2022, I focused on developing and operating a recommendation system, and I am currently studying LLM and looking for new business opportunities. In particular, in April of this year, I developed EVAL, the world's first LLM Agent that can do web development, and it became a global issue. In order to better utilize LLM, I am continuously following up on recent research, testing new ideas, and planning new functions for the product. I am so honored to have the opportunity to share my experiences with many people. I will make sure that my presentation will provide you with new perspectives.

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