From Classical ML to Transformers

Join the Department of Statistics for a seminar featuring Dr. Amir Jafari, assistant professor of data science at George Washington University.

Abstract:

This talk presents a complete journey through the evolution of artificial intelligence and machine learning, from foundational classical algorithms like decision trees, random forests and support vector machines to cutting-edge transformer architectures and large language models such as GPT and BERT.

Designed for students, researchers and industry professionals, the seminar covers real-world applications across healthcare, finance, retail, transportation and emerging fields like climate science and smart cities, while exploring the technical evolution from neural networks to deep learning breakthroughs in computer vision, natural language processing and speech processing.

Participants will have the opportunity to engage with hands-on demonstrations through an interactive Streamlit application featuring model training comparisons, attention mechanism visualizations and image processing tools, gaining understanding of current state-of-the-art capabilities, training dynamics, computational requirements and future implications including multimodal AI, responsible development and societal impact.

The seminar provides essential insights into the rapidly evolving landscape of data science and AI, preparing attendees to understand and contribute to this transformative field that is reshaping how we interact with and understand the world.