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MLOps.community

Weekly talks and fireside chats about everything that has to do with the new space emerging around D

Episodes

Total: 453

Analyzing the Google Paper on Continuous Delivery in ML // Part 4 // MLOps Coffee Sessions #17
2020/11/3

MLOps level 2: CI/CD pipeline automation For a rapid and reliable update of the pipelines in product

Hands-on serving models using KFserving // Theofilos Papapanagiotou // Data Science Architect at Prosus // MLOps Meetup #40
2020/10/30

MLOps community meetup #40! Last Wednesday, we talked to Theofilos Papapanagiotou, Data Science Arch

Operationalize Open Source Models with SAS Open Model Manager // Ivan Nardini // Customer Engineer at SAS // MLOps Meetup #39
2020/10/27

MLOps community meetup #39! Last week we talked to Ivan Nardini, Customer Engineer at SAS, about Ope

Machine in Production = Data Engineering + ML + Software Engineering // Satish Chandra Gupta // MLOps Coffee Sessions #16
2020/10/26

//Bio Satish built compilers, profilers, IDEs, and other dev tools for over a decade. At Microsoft R

MLOps + Machine Learning // James Sutton // MLOps Coffee Sessions #15
2020/10/20

James Sutton is an ML Engineer focused on helping enterprise bridge the gap between what they have n

Scalable Python for Everyone, Everywhere // Matthew Rocklin // MLOps Meetup #38
2020/10/19

Parallel Computing with Dask and Coiled Python makes data science and machine learning accessible to

MLOps Coffee Sessions #13 How to Choose the Right Machine Learning Tool: A Conversation // Jose Navarro and Mariya Davydova
2020/10/18

This time we talked about one of the most vibrant questions for any MLOps practitioner: how to choos

MLOps Coffee Sessions #14 Conversation with the Creators of Dask // Hugo Bowne-Anderson and Matthew Rocklin
2020/10/12

Dask What is it? Parallelism for analytics What is parallelism? Doing a lot at once by splitting tas

MLOps Coffee Sessions #12: Journey of Flyte at Lyft and Through Open-source // Ketan Umare
2020/10/10

Why was Flyte built at Lyft? What sorts of requirements does a ML infrastructure team have at lyft?

MLOps Coffee Sessions #11: Analyzing “Continuous Delivery and Automation Pipelines in ML" // Part 3
2020/10/4

Round 3 analyzing the Google paper "Continuous Delivery and Automation Pipelines in ML" // Show Note

MLOps Meetup #36: Moving Deep Learning from Research to Prod Using DeterminedAI and Kubeflow // David Hershey, DeterminedAI
2020/10/4

MLOps community meetup #36! This week we talk to David Hershey Solutions Engineer at Determined AI,

MLOps Coffee Sessions #10 Analyzing the Article “Continuous Delivery and Automation Pipelines in Machine Learning" // Part 2
2020/9/22

Second installation David and Demetrios reviewing the google paper about Continuous training and aut

MLOps Meetup #34: Streaming Machine Learning with Apache Kafka and Tiered Storage // Kai Waehner, Confluent
2020/9/17

MLOps Meetup #34! This week we talk to Kai Waehner about the beast that is apache kafka and how many

MLOps Meetup #33 Owned By Statistics: How Kubeflow & MLOps Can Help Secure Your ML Workloads // David Aronchick - Head of Open Source ML Strategy at Azure
2020/9/14

While machine learning is spreading like wildfire, very little attention has been paid to the ways t

MLOps Coffee Sessions #9 Analyzing the Article “Continuous Delivery and Automation Pipelines in Machine Learning “ // Part 1
2020/9/14

In this last episode, we covered how Google is thinking about MLOps and how automation plays a key p

MLOps Meetup #32 Building Say Less: An AI-Powered Summarization App // Yoav Zimmerman - Founder of Model Zoo
2020/9/8

Yoav is the builder behind Say Less, an AI-powered email summarization tool that was recently featur

MLOps Coffee Sessions #8 // MLOps from the Perspective of an SRE // Neeran Gul
2020/9/8

|| Links Referenced in the Show || General Info: https://medium.com/@paktek123 Load Balancer Series:

MLOps Meetup #31 // Creating Beautiful Ambient Music with Google Brain’s Music Transformer // Daniel Jeffries - Chief Technology Evangelist at Pachyderm
2020/9/5

We trained a Transformer neural net on ambient music to see if a machine can compose with the great

MLOps Coffee Sessions #7 // MLOps and DevOps - Parallels and Deviations // Featuring Damian Brady
2020/8/31

MLOps and DevOps have a large number of parallels. Many of the techniques, practices, and processes

MLOps Meetup #30 // Path to Production and Monetizing Machine Learning // Vin Vashishta - Data Scientist | Strategist | Speaker & Author
2020/8/20

The concept of machine learning products is a new one for the business world. There is a lack of cla