Session Spotlight
I'm a Developer not a Data Scientist: How do I leverage LLM's?
Wednesday, January 31, 2024 - 2:30 PM CST, for 1 hour.
Regular, 60 minute presentation
Room: Campsite 5
As a developer, you may feel intrigued by the potential of Large Language Models (LLMs) like GPT-3 and GPT-4 but wonder how to effectively leverage them without extensive data science expertise. In this talk, we will guide developers on harnessing the power of LLMs and incorporating them into their projects. LLMs offer incredible capabilities for natural language processing, content generation, and more. However, you don't need to be a data scientist to tap into their potential. We will explore practical strategies and tools that empower developers to work with LLMs efficiently and effectively. Join us as we discuss techniques for data preparation, model selection, and fine-tuning LLMs to suit your specific needs. We will explore user-friendly libraries, APIs, and pre-trained models that simplify the integration process, allowing developers to focus on their core expertise. Additionally, we will address common challenges developers may encounter when working with LLMs. By understanding these challenges and learning best practices, developers can navigate potential pitfalls and optimize their use of LLMs. Through hands-on demonstrations and real-world examples, we will showcase how developers can leverage LLMs in various applications. You will leave this talk equipped with practical knowledge and resources to start incorporating LLMs into your projects immediately. Join us to discover how, as a developer, you can unlock the power of LLMs and enhance your applications with cutting-edge natural language processing capabilities. Embrace the potential of LLMs without the need for extensive data science expertise and take your projects to new heights.
Prerequisites
Experienced developer
Take Aways
- Developers can effectively leverage LLMs without extensive data science expertise.
- Techniques for data preparation, model selection, and fine-tuning LLMs will be discussed.
- Hands-on demonstrations and real-world examples will showcase how developers can leverage LLMs in various applications.