Intermediate Lessons

Cost Optimization and Performance // LLMs in Production Conference Panel Discussion 2

What is the role of ML Engineers in the time of GPT4 and BARD? // Hannes Hapke // LLMs in Prod Con

From Idea to Product: The Development of Apache Spark

Generative Interfaces Beyond Chat // Linus Lee // LLMs in Production Conference

Machine Learning Education at Uber // Melissa Barr & Michael Mui // MLOps Podcast #156

Promoting Distributed Innovation // Melissa Barr & Michael Mui // MLOps Podcast #154 video clip

Building Machine Learning Workflows: Lessons Learned

Understanding User Needs in Machine Learning and AI Development

Spark and MLflow Similarities // Matei Zaharia // MLOps Podcast #155 short clip

Age of Industrialized AI // Dan Jeffries // LLMs in Production Conference

The Future of Scalability in Machine Learning: Predictions and Challenges

The Birth and Growth of Spark: An Open Source Success Story // Matei Zaharia // MLOps Podcast #155

Deep Learning in Google Maps

Challenges and Opportunities in Building Data Science Solutions with LLMs // QuantumBlack Roundtable

Want High Performing LLMs? Hint: It is All About Your Data // Vikram Chatterji // LLMs in Prod Con

Solving the Last Mile Problem of Foundation Models with Data-Centric AI //Alex Ratner // LLM in Prod

ML Scalability Challenges // Waleed Kadous // MLOps Podcast # 154

Formula for Successful Jupyter Notebook Deployment // Keith Trnka // MLOps Podcast #148 short clip

Tecton 0.6: Notebook-driven Development // Jason Dunne // MLOps Meetup #122

The Future of Data Science Teams: A World Without Data Teams?

Balancing Technical Debt and Future Thinking in Product Development

The Challenge of Dynamic AI Models in the Real World

Enabling Rapid Updates of Models: Parallels with Software and Security

Addressing Latency Challenges in Large Language Models

ML in Production: A DS from Ubisoft Perspective // Jean-Michel Daignan // MLOps Podcast #151

Large Language Models in Production Round-table Conversation

The Trustworthy Chatbot Search Engine // Saahil Jain // MLOps Podcast #151 clip

Optimizing ML Capabilities for Business Success // Jason McCampbell // MLOps Podcast #149 clip

The Value of Communication in the Age of Machine Learning

Differences in Challenges Faced by Staff Engineers in Startups and Large Organizations

Rewarding Behavior with Machine Learning // Niall Murphy // MLOps Podcast #127 reels

Building a Centralized Background for Seamless User Experience

AWS Dev and Pro Management // Sahil Khanna // MLOps Podcast #145 clip

Predictions for Future Changes in the Python Programming Language

Balancing Opinions and Data in Tool-Focused Companies #shorts

Managing Data on DAG Store // Stephen Bailey // MLOps Podcast #141 video clip

Navigating the Management Side of Machine Learning Research #shorts

Explainability in the MLOps Cycle // Dattaraj Rao // MLOps Podcast #138

Creative AI - Using ML to Create Art, Music, and Jokes // Suyash Joshi // MLOps Meetup #113

MLflow Pipelines: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112

Making MLFlow // Lead MLFlow Maintainer Corey Zumar // MLOps Coffee Sessions #103

Building a Movie Recommendation System on Tecton with Snowflake // David Hershey //MLOps Meetup #102

MLOps at Stripe // Emmanuel Ameisen // MLOps Coffee Sessions #85

Building an Open Source MLOps Stack with ZenML // Hamza Tahir // MLOps Workshop Meetup # 92

Build a Culture of ML Testing and Model Quality // Mohamed Elgendy // MLOps Coffee Sessions #76

Just Build It! Tips for Making ML Engineering and MLOps Real // Andy McMahon // MLOps Meetup #91

Building for Small Data Science Teams // James Lamb // MLOps Coffee Sessions #69

What is Kubeflow? // Aniruddha Choudhury // Meetup #72 short clip