Intermediate Lessons

September Reading group clip 1

How to Use Differential Privacy in Your AI Prompts

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

Engineering Your AI Platform // Panel // DE4AI

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

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

How To Cut Your Data Infrastructure Costs in Half

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

Building a Data Infrastructure for AI/ML

How Feature Stores Work // Simba Khadder // DE4AI

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

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

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

Why We Need to Rethink Frameworks

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

RAG Quality Starts with Data Quality // Adam Kamor // MLOps Podcast #262

Critical Importance of Vulnerability Scanning in Software Development // Harcharan Kabbay // shorts

The Future of Multimodal Models in Technology // Markus Stoll // MLOps Podcast #258 clip

Who's MLOps for Anyway? // Jonathan Rioux // MLOps Podcast #261

Alignment is Real // Shiva Bhattacharjee // MLOps Podcast #260