Browse Lessons

Operationalizing Machine Learning at a Large Financial Institution // Daniel Stahl //MLOps Meetup#56

What’s changed in the MLOps ecosystem? Explained by the Godfather of MLOps // Coffee Session Clip

How to Avoid Suffering in MLOps/Data Engineering Role // Igor Lushchyk // MLOps Meetup #55

Product Management in Machine Learning // Laszlo Sragner // MLOps Meetup #54

Does anyone know of a good way to manage dependencies? // MLOps Coffee Sessions #31 Part 2 Clip

MLOps Engineering Labs Recap // Part 2 // MLOps Coffee Sessions #31

How Explainable AI is Critical to Building Responsible AI // Krishna Gade // MLOps Meetup #53

The Power of Explainable AI // Krishna Gade // MLOps Meetup #53 short clip

MLOps Engineering Labs Recap // Part 1 // MLOps Coffee Sessions #30

'Git for Data' - Who, What, How and Why? // Luke Feeney & Gavin Mendel-Gleason // MLOps Meetup #52

Agile AI Ethics: Balancing Short Term Value with Long Term Ethical Outcomes // Pamela Jasper // #51

Culture and Architecture in MLOps // Jet Basrawi // MLOps Coffee Sessions #29

2 tools = 90% operational ML // Michael Del Balso -Willem Pienaar - David Aronchick // MLOps #50

Machine Learning Design Patterns for MLOps // Valliappa Lakshmanan // MLOps Meetup #49

Lessons Learned From Hosting the ML Engineered Podcast // Charlie You // MLOps Coffee Sessions #28

Practical MLOps // Noah Gift // MLOps Coffee Sessions #27

Serving ML Models at a High Scale with Low Latency // Manoj Agarwal // MLOps Meetup #48

Ep#9 - Private data Data Science friendly

Machine Learning Feature Store Panel Discussion // MLOps Coffee Sessions #26

ProductizeML: Assisting Your Team to Better Build ML Products // Adrià Romero // MLOps Meetup #47

Ep#8 - The revolution of Federated Learning

Most Underrated MLOps Topics // Marian Ignev // MLOps Coffee Sessions #25

Real-time Feature Pipelines, A Personal History // Hendrik Brackmann // MLOps Meetup #46

MLOps Feature Store Explanation

Machine Learning Design Patterns // Sara Robinson // MLOps Coffee Sessions #24

Santa's Feature Store // MLOps Christmas

MLOps Community // For The Community, By The Community

SRE for ML Infra // Todd Underwood // MLOps Coffee Sessions #23

How To Move From Barely Doing BI to Doing AI // Joe Reis // MLOps Meetup #45

Deep in the Heart of Data // Carl Steinbach // MLOps Coffee Sessions #22

Ep#7 - ML and Encryption - It's all about secure insights

Ep#6 - Privacy-preserving ML with Differential Privacy

Human-centric ML Infrastructure: A Netflix Original // Savin Goyal // MLOps Meetup #44

A Conversation with Seattle Data Guy // Benjamin Rogojan // MLOps Coffee Sessions #21

Monzo Bank - An MLOps Case Study // Neal Lathia // MLOps Coffee Sessions #20

Ep#5 - The intersection between DataOps and privacy

When to Build and When to Buy // Nathan Benaich // MLOps Meetup #7

Ep#4 - Are Privacy-enchancing technologies a myth?

MLOps Matures With Companies Doing ML

Introducing Data Downtime: From Firefighting to Winning // Barr Moses // MLOps Coffee Sessions #19

The Current MLOps Landscape // Nathan Benaich & Timothy Chen // MLOps Meetup #43

Ep#3 - AI an ethical dilemmas

UN Global Platform // Mark Craddock // Co-Founder & CTO, Global Certification // MLOps Meetup #42

Ep#2 - What are regulations saying about data privacy?

Metaflow: Supercharging Our Data Scientist Productivity // Ravi Kiran Chirravuri // MLOps Meetup #41

Luigi in Production // MLOps Coffee Sessions #18 // Luigi Patruno ML in Production

When Machine Learning meets privacy - Episode 1

CI/CD & Continuous Training in ML // Part 4 // MLOps Coffee Sessions #17