AI and LLM Solutions Building on Databricks: Key Concepts of the End-to-End AI Lifecycle, from Data Preparation and Model Building to Deployment, Monitoring, and MLOps
Data preparation for model training: Learn how to load and process data for AI workloads.
Feature engineering: Use Unity Catalog to create feature tables and track feature lineage.
Training and registration of models: Use AutoML for efficient training and tuning of ML models.
Production real-time or batch serving: Start using model serving for real-time workloads or deploy MLflow models for offline inference.
Self-hosting large language models (LLMs): Securely and cost-effectively host open-source LLMs within the Databricks environment.
Monitoring deployed models: Continuously capture and log Model Serving endpoint inputs and predictions.
Bundle assets for programmatic deployment: Use Databricks Asset Bundles for efficient packaging and deployment of data and AI assets.
End-to-end MLOps: Combine DataOps, ModelOps, and DevOps for end-to-end ML and LLM operations.
About the Presenter
Venkata Jyothi Kotra : Venkata Jyothi Kotra is the Director of Data & AI at Focal CXM, where she leads Data & AI Solutions for the commercial an public sector. Additionally, she is an adjunct faculty member in Data Analytics at South New Hampshire University. With a deep focus on data modernization, architecture, governance, and enterprise data modeling, Ms. Kotra integrates data, analytics, and machine learning to drive decisions in sales, marketing, finance, and operations. Her areas of expertise include big data, cloud computing, distributed data processing, system upgrades, and business process transformation.
FocalCXM is a software product development services company with a portfolio of innovative SaaS services to re-engineer CRM/CX processes for enterprises worldwide. With a laser focus on specific industries, FocalCXM is passionate about collaborating with customers and partners in solving their problems; one industry process at a time.