Understanding LLMs for Code Generation
Key Takeaways:- Learn how large language models generate text.
- The inherent challenges of LLMs for code generation.
- Prompt engineering strategies for code generation.
Description
Over the past year, Large Language Models (LLMs) have showcased remarkable natural language capabilities, setting new standards in Natural Language Processing and fueling the development of LLM-powered applications. As interest in leveraging LLMs for coding tasks continues to grow, companies are pushing the boundaries by transforming natural language into code generation, resulting in products like GitHub Copilot.
In this session, Andrea and Josep will explore the role of LLMs for coding tasks, focusing on hands-on examples that demonstrate effective prompt engineering techniques to optimize code generation. Whether you're interested in understanding how models work for coding or looking for ways to streamline your coding workflow, this session will provide with the insights and practical skills to fully utilize the potential of LLMs for coding.
Presenter Bio
Andrea Valenzuela is currently working on the CMS experiment at the particle accelerator (CERN) in Geneva, Switzerland. With expertise in data engineering and analysis for the past six years, her duties include data analysis and software development. She is now working towards democratizing the learning of data-related technologies through the Medium publication ForCode'Sake.
She holds a BS in Engineering Physics from the Polytechnic University of Catalonia, as well as an MS in Intelligent Interactive Systems from Pompeu Fabra University. Her research experience includes professional work with previous OpenAI algorithms for image generation, such as Normalizing Flows.
Josep is a Data Scientist and Project Manager at the Catalan Tourist Board, using data to improve the experience of tourists in Catalonia. His expertise includes the management of data storage and processing, coupled with advanced analytics and the effective communication of data insights.
He is also a dedicated educator, teaching the Big Data Master's program at the University of Navarra, and regularly contributing insightful articles on data science to Medium and KDNuggets.
He holds a BS in Engineering Physics from the Polytechnic University of Catalonia as well as an MS in Intelligent Interactive Systems from Pompeu Fabra University.
Currently, he is passionately committed to making data-related technologies more accessible to a wider audience through the Medium publication ForCode'Sake.