Browse Lessons

Balancing Technical Expertise and Motivation in ML Interviews

Balancing Opinions and Data in Tool-Focused Companies #shorts

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

Exploring Customer Needs for Electric Vehicles through Twitter Data Mining #shorts

Navigating the Management Side of Machine Learning Research #shorts

The Hype and Realities of Machine Learning #shorts

Accelerating Data Centric Development with GPT-3: Smaller and Cheaper Deployment Models

The Adaptation Gap: Bridging the Gap between Generalist and Specialized Models

Challenges and Concerns of Using GPT-3 in Enterprise Settings // Alex Ratner // MLOps Podcast Shorts

Applying Machine Learning to DNA Storage and Decoding // Luis Ceze // MLOps Podcast Shorts

The Motivation for MLOps // Steven Fines // MLOps Meetup #118

Foundational Models are the Future but... with Alex Ratner CEO of Snorkel AI // MLOps Podcast #139

Vertex AI Workshop // Sascha Heyer // MLOps Meetup #117

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

Facebook Marketplace Machine Learning System Design Review

Machine Learning Operations — What is it and Why Do We Need It? // Niklas Kühl // MLOps Podcast #137

Building an Open Source MLOps Stack with ZenML Part 2 // Hamza Tahir // MLOps Meetup # 116

Systems Engineer Navigating the World of ML // Andrew Dye // MLOps Podcast #136

"Real-Time" ML: Features and Inference // Sasha Ovsankin and Rupesh Gupta // MLOps Podcast #135

Building Threat Detection Systems: An MLE's Perspective // Jeremy Jordan // MLOps Podcast #134

Driving ML Data Quality with Data Contracts // Andrew Jones // MLOps Meetup #115

MLOps in Practice: Common Challenges and Lessons Learned / Marouen Hizaoui & Mo Basirati/Meetup #114

Real-time Machine Learning with Chip Huyen // MLOps Coffee Sessions #133

What is Data / ML Like on League? // Ian Schweer // MLOps Coffee Sessions #132

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

Let's Continue Bundling into the Database // Ethan Rosenthal // MLOps Coffee Sessions #131

Unleashing Sensitive Datasets with Distributed Data Science // Blaise Thomson // MLOps Meetup #112

MLOps for Ad Platforms // Andrew Yates // MLOps Coffee Sessions #130

Applying DevOps Practices in Data and ML Engineering // Antoni Ivanov // MLOps Meetup #111

Voice and Language Tech // Catherin Breslin // Coffee Sessions #129

Managing Machine Learning Projects // Simon Thompson // MLOps Coffee Sessions #128

Obtain New Insights on Model Behavior with Fiddler // Danny Brock // MLOps Meetup #110

Reliable Machine Learning // Niall Murphy & Todd Underwood // Coffee Sessions #127

ML Unicorn Start-up Investor Tells-IT-All // George Mathew // MLOps Coffee Sessions #126

Databricks Model Serving V2 // Rafael Pierre // Coffee Sessions #125

Monitoring Unstructured Data // Aparna Dhinakaran & Jason Lopatecki // Lightning Sessions #2

Trustworthy Machine Learning // Kush Varshney // Coffee Sessions #124

RECOMMENDER SYSTEM: Why They Update Models 100 Times a Day // Gleb Abroskin // MLOps Coffee Ses #123

Scaling Similarity Learning at Digits // Hannes Hapke // Coffee Sessions #122

Bringing DevOps Agility to ML // Luis Ceze // Coffee Sessions #121

Feathr: LinkedIn's High-performance Feature Store // David Stein // Coffee Sessions #120

MLOps at DoorDash // Hien Luu and DoorDash Leads // Coffee Sessions #119

ML Platforms, Where to Start? // Olalekan Elesin // Coffee Sessions #118

From Expectations to Synthetic Data Generation // Fabiana Clemente // MLOps Meetup #109

Data Engineering for ML // Chad Sanderson // Coffee Sessions #117

Scaling Machine Learning with Data Mesh // Shawn Kyzer // Coffee Sessions #116

How Hera is an Enabler of MLOps Integrations // Flaviu Vadan // Coffee Sessions #115

Product Enrichment and Recommender Systems // Marc Lindner and Amr Mashlah // Coffee Sessions #114