Browse Lessons

Scrappy Startup Secrets Build or Buy Dilemma!

September Reading group clip 1

How to Use Differential Privacy in Your AI Prompts

The Future of Data: Composability & the Modular Data Stack

Scaling Data Reliably: A Journey in Growing Through Data Pain Points // Miriah Peterson // DE4AI

Chronon: Airbnb's Open-Source Data Platform

The Next Revolution in AI: LLMs and Beyond

How GPUs are Revolutionizing AI Data Management

Data Contracts: The Missing Piece of the Data Puzzle

Data Engineering: The Missing Piece of Your Data Science Puzzle

Common ML Serving Architectures Explained

Data Quality Management Techniques - The Complete Guide

How to Make Your Data Science Reproducible (and Why You Should Care)

The Future of Software Architecture for GenAI: Real-Time Data Streaming

How Data Capture Transforms ML Observability

Real-Time Event Processing for AI/ML with Numaflow // Sri Harsha Yayi // DE4AI

The Evolution of Lyft's Feature Store // Devon Mittow // DE4AI

Engineering Your AI Platform // Panel // DE4AI

The Only Constant is (Data) Change // Panel // DE4AI

Data Scientists & Data Engineers: How the Best Teams Work // Panel // DE4AI

Partnering with Product for Effective, quality Data Ingestion & Training Data // Daniela Santisteban

AI-Powered Data Unification for Data Platforms // Shelby Heinecke // DE4AI

Putting the AI back in Medallion Lake Design // Simon Whiteley

Supercharging Your RAG System: Techniques and Challenges // Tengyu Ma // DE4AI

How To Cut Your Data Infrastructure Costs in Half

Why DuckDB is the Future of Data

Turn Data Chaos into AI Strategy with Programmatic AI Data Development // Elena Boiarskaia // DE4AI

LLMs in Financial Services: Personalized Portfolio Recommendation Engines // Akmal Chaudhri // DE4AI

From Notebook to Kubernetes: Scaling GenAI Pipelines with ZenML // Alex Strick van Linschoten

DuckDB is fast for analytics, but what can it do for AI? // Mehdi Ouazza // DE4AI

GenAI in production with MLflow // Ben Wilson // DE4AI

Unified Data + AI Governance with Unity Catalog // Michelle Leon & Victoria Bukta // DE4AI

Building a Data Infrastructure for AI/ML

11 lessons learned from doing deployments // Sol Rashidi // DE4AI

How Feature Stores Work // Simba Khadder // DE4AI

Building Hyper-Personalized LLM Applications with Rich Contextual Data // Mike Del Balso // DE4AI

The Daft distributed Python data engine: multimodal data curation at any scale // Jay Chia // DE4AI

Centralized or Decentralized ML Platform? // Jelmer Borst and Daniela Solis // MLOps Podcast #267

Making Your Company LLM-native // Francisco Ingham // MLOps Podcast #266

Boosting LLMs: Performance, Scaling, and Structured Outputs // MLOps Mini Summit #8

Why We Need to Rethink Frameworks

The Shift in Data Dynamics // Shiva Bhattacharjee // MLOps Podcast #260 clip

Unpacking 3 Types of Feature Stores // Simba Khadder // MLOps Podcast #265

Integrating Knowledge Graphs & Vector RAG for Efficient Information Extraction / Reading Grp Sept 12

Reinvent Yourself and Be Curious // Stefano Bosisio // MLOps Podcast #264

Transforming API Output Quality with Assertions // Vikram Rangnekar // MLOps Podcast #259 clip

Data Quality and Tonic Textual // Adam Kamor // MLOps Podcast #262 clip

Global Feature Store // Gottam Sai Bharath & Cole Bailey // MLOps Podcast #263