sujee.dev
My Conference Talks
2024
2024-12-04: PyData Global 2024, Online
Preparing Data for LLM Applications Using Data Prep Kit
Gave a presentation and demo on Data Prep Kit - an open source toolkit to help prepare data for LLM applications.
Conference • My session • Session recording • session details pdf
2024-10-26: AI Summit, Mountain View, CA
Preparing Data for LLM Applications Using Data Prep Kit
Gave a presentation and demo on Data Prep Kit - an open source toolkit to help prepare data for LLM applications.
Conference • session • session details pdf (cached) • session details png (cached) • workshop resources
linkedin post 1 & testimonials • linkedin post 2 • linkedin post 3
2024-10-21: IBM TechXchange, Las Vegas, NV
Streamlining Data Prep for LLMs with Data Prep Kit with Dave Nielsen, Head of AI Alliance Community, IBM
Talk and workshop introducing Data Prep Kit - an open source toolkit to help prepare data for LLM applications.
conf • session details • session details 1 (cached) • session details 2 (cached) • workshop code
2024-02-21: Developer Week, Oakland, CA
Vector Search + LLMs with Dave Nielsen of MongoDB
Talked about Vector Search, LLMs and RAG. Demoed applications featuring Vector Search using MongoDB Atlas and RAG application of querying PDFs using LLMs
conf link 1 • conf link 2 • speaker page 1 • speaker page 2 • linkedin post • pic •
2024-01-31: AI User Conference, San Francisco, CA
Vector Search + LLMs with Dave Nielsen of MongoDB
Talked about Vector Search, LLMs and RAG. Demoed applications featuring Vector Search using MongoDB Atlas and RAG application of querying PDFs using LLMs
conf link 1 • conf link 2 • speaker page 1 • speaker page 2 • code
2017
2017-11: AWS re:Invent, Las Vegas, NV
Presented Intel’s BigDL framework
Evangelized BigDL framework from Intel. I created videos, code samples
conf presentation • code repository • Docker image
2017: Intel AI Dev Conference
Presented my work of Intel’s BigDL framework
2017: ODSC West Conference
Apache Spark - a hands on workshop
Presented Spark for large data analytics
