Browse Lessons

How many models in prod til I need a dedicated ML platform?

More difficult transition for data scientists to become ML engineers

Speed, Trust, Evolution and Scale in MLOps

Dependable data and being able to Trust in your Data with Venkata Pengali of Scribble Data

Venkata Pingali of Scribble Data Thoughts on the Current State of Machine Learning

Who has the highest standards in ML?

Resume driven development in Machine learning & software engineering

Swiss Cheese model in Machine Learning

Survivorship Bias in machine learning tutorials

Learning from real life Machine Learning failures

Humans in the Loop are a defining factor in Machine Learning

Current State Of Machine Learning

Specific challenges in Machine Learning

MLOps: Airflow Pros and Cons

MLOps meetup #5 High Stakes ML: Active Failures, Latent Factors with Flavio Clesio

MLOps Meetup #6: Mid-Scale Production Feature Engineering with Dr. Venkata Pingali

3 key parts to Machine Learning monitoring

Auto retrain ML models is not the question

Developing a Machine Learning Feature Store

Evolution of the ML feature store @SurveyMonkey

Doing ML with Personal Information

How do you handle ML version control at SurveyMonkey

Hybrid Data Science Teams @SurveyMonkey

MLOps #4: Shubhi Jain - Building an ML Platform @SurveyMonkey

Message buses, Async and sync architecture

ML Services Gateway at SurveyMonkey

ML Platforms - The build vs buy question

ML tooling in large companies

MLOps Problems in different size companies

Friction Between Data Scientists and Software Engineers

Provenance and Reproducibility in Machine Learning; what is it and why you need it?

How Phil Winder got into Data Science and Software Engineering

MLOps and Monitoring

Bare necessities for getting an ML model into production

Hierarchy of MLOps Needs

Building an MLOps Team? Key ideas to keep in mind

Automatically Retrain Machine Learning Models? Are best practices worth it?

Hierarchy of Machine Learning Needs // Phil Winder // MLOps Meetup #3

Explainability, Black boxes and EU white paper on reproducibility

Life purpose and too many spreadsheets

What Does Best in Class AI/ML Governance Look Like in Fin Services? // Charles Radclyffe // MLOps #2

MLOps lifecycle description

MLOps Manifesto with Luke Marsden from Dotscience

Remote Collaboration as a Data Scientist

Our 1st MLOps Meetup // Luke Marsden // MLOps Meetup #1