Diana Pholo
My name is Diana Pholo and I am passionate about research, teaching and data science.
In 2014, obtained a Masters in electronics from ÉCOLES Supérieure d'Ingénieurs en Électronique et Électrotechnique
(ESIEE).
I am currently working on getting a PhD while working as a
part-time data scientist at Predictive Insights.
I am also a full-time Chief-Mom-Officer.
Accepted Talks:
Effective prompt engineering for Python programmers
The world of technology is witnessing a transformation powered by Large Language Models (LLMs) like ChatGPT and Bing AI. These marvels of AI are reshaping how we interact with machines as they can comprehend and generate human-like text. But to get the most out of these models, you must learn to ask the right question.
Prompt engineering is the art of crafting specific instructions for LLMs. It molds the language model's responses, making them more accurate, relevant, and actionable. Our session will delve into the essence of prompt engineering, addressing its significance for programmers and its role in improving model outputs and reducing biases. We'll explore a variety of prompt types, and offer practical tips for optimisation. Additionally, we'll navigate through real-world case studies, showcasing the tangible impact of prompt engineering on programming tasks. If you're intrigued by the potential of LLMs and eager to harness their power effectively, this presentation is your gateway to unlocking their true potential in your projects.
