MLOps.community

By Demetrios Brinkmann

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.

  1. 1.
    Tour of Upcoming Features on the Hugging Face Model Hub // Julien Chaumond // MLOps Coffee Sessions #48
    52:15
  2. 2.
    Fast.ai, AutoML, and Software Engineering for ML: Jeremy Howard // Coffee Session #47
    57:54
  3. 3.
    Learning from 150 Successful ML-enabled Products at Booking.com // Pablo Estevez // Coffee Sessions #46
    56:43
  4. 4.
    Machine Learning in Cyber Security // Monika Venckauskaite // MLOps Meetup #70
    53:41
  5. 5.
    Enterprise Security and Governance MLOps // Diego Oppenheimer // MLOps Coffee Sessions #45
    53:34
  6. 6.
    Autonomy vs. Alignment: Scaling AI teams to deliver value // Grant Wright // MLOps Coffee Sessions #44
    50:51
  7. 7.
    How Pinterest Powers Image Similarity // Shaji Chennan Kunnummel // System Design Reviews #1
    57:36
  8. 8.
    Engineering MLOps // Emmanuel Raj // MLOps Meetup #69
    51:54
  1. 9.
    Project/Product Management for MLOps // Korri Jones - Simarpal Khaira - Veselina Staneva // MLOps Meetup #68
    57:26
  2. 10.
    Maturing Machine Learning in Enterprise // Kyle Gallatin // MLOps Coffee Sessions #43
    47:19
  3. 11.
    Practical MLOps Part 2 // Alfredo Deza // MLOps Meetup #66
    1:01:37
  4. 12.
    Common Mistakes in the ML Development Lifecycle // Kseniia Melnikova // MLOps Meetup #65
    54:30
  5. 13.
    Model Performance Monitoring and Why You Need it Yesterday // Amit Paka // MLOps Coffee Sessions #42
    1:07:01
  6. 14.
    CI/CD in MLOPS // Monmayuri Ray // MLOps Coffee Sessions #41
    50:36
  7. 15.
    Operationalizing Machine Learning at Scale // Christopher Bergh // MLOps Meetup #64
    57:38
  8. 16.
    Scaling AI in production // Srivatsan Srinivasan // MLOps Coffee Sessions #40
    52:08
  9. 17.
    MLOps: A leader's perspective // Stephen Galsworthy // MLOps Coffee Sessions #39
    54:20
  10. 18.
    Learnings from Live Coding: An MLOps Project on Twitch // Felipe Campos Penha // MLOps Meetup #63
    50:15
  11. 19.
    Law of Diminishing Returns for Running AI Proof-of-Concepts // Oguzhan Gencoglu // MLOps Meetup #62
    56:22
  12. 20.
    Organisational Challenges of MLOps // Adam Sroka // MLOps Coffee Sessions #38
    54:39
  13. 21.
    From Idea to Production ML // Lex Beattie - Michael Munn - Mike Moran // MLOps Meetup #61
    53:22
  14. 22.
    MLOps Memes // Ariel Biller // MLOps Coffee Sessions #37
    1:00:42
  15. 23.
    Luigi in Production Part 2 // Luigi Patruno // MLOps Coffee Sessions #36
    59:04
  16. 24.
    War Stories Productionising ML // Nick Masca // Coffee Session #35
    51:02
  17. 25.
    Deploying Machine Learning Models at Scale in Cloud // Vishnu Prathish // MLOps Meetup #60
    57:57
  18. 26.
    Machine Learning at Atlassian // Geoff Sims // Coffee Session#34
    58:34
  19. 27.
    MLOps Community 1 Year Anniversary! // Demetrios Brinkmann, David Aponte & Vishnu Rachakonda // MLOps Meetup #59
    59:28
  20. 28.
    MLOps Investments // Sarah Catanzaro // Coffee Session #33
    46:29
  21. 29.
    Model Watching: Keeping Your Project in Production // Ben Wilson // MLOps Meetup #58
    53:13
  22. 30.
    A Missing Link in the ML Infrastructure Stack // Josh Tobin // MLOps Meetup #57
    56:08
  23. 31.
    The Godfather Of MLOps // D. Sculley // MLOps Coffee Sessions #32
    51:35
  24. 32.
    Operationalizing Machine Learning at a Large Financial Institution // Daniel Stahl // MLOps Meetup #56
    1:05:03
  25. 33.
    How to Avoid Suffering in Mlops/Data Engineering Role // Igor Lushchyk // MLOps Meetup #55
    57:55
  26. 34.
    Product Management in Machine Learning // Laszlo Sragner // MLOps Meetup #54
    57:55
  27. 35.
    MLOps Engineering Labs Recap // Part 2 // MLOps Coffee Sessions #31
    1:04:26
  28. 36.
    How Explainable AI is Critical to Building Responsible AI // Krishna Gade MLOps // Meetup #53
    56:56
  29. 37.
    MLOps Engineering Labs Recap // Part 1 // MLOps Coffee Sessions #30
    59:38
  30. 38.
    'Git for Data' - Who, What, How and Why? // Luke Feeney - Gavin Mendel-Gleason // MLOps Meetup #52
    57:50
  31. 39.
    Agile AI Ethics: Balancing Short Term Value with Long Term Ethical Outcomes // Pamela Jasper // MLOps Meetup #51
    1:06:54
  32. 40.
    Culture and Architecture in MLOps // Jet Basrawi // MLOps Coffee Sessions #29
    53:53
  33. 41.
    2 tools to get you 90% operational // Michael Del Balso - Willem Pienaar - David Aronchick // MLOps Meetup #50
    56:43
  34. 42.
    Machine Learning Design Patterns for MLOps // Valliappa Lakshmanan // MLOps Meetup #49
    56:46
  35. 43.
    Lessons Learned From Hosting the Machine Learning Engineered Podcast // Charlie You // MLOps Coffee Sessions #28
    1:04:37
  36. 44.
    Practical MLOps // Noah Gift // MLOps Coffee Sessions #27
    58:48
  37. 45.
    Serving ML Models at a High Scale with Low Latency // Manoj Agarwal // MLOps Meetup #48
    56:17
  38. 46.
    When Machine Learning meets privacy - Episode 9
    41:38
  39. 47.
    Machine Learning Feature Store Panel Discussion // MLOps Coffee Sessions #26
    1:05:31
  40. 48.
    ProductizeML: Assisting Your Team to Better Build ML Products // Adrià Romero // MLOps Meetup #47
    50:56
  41. 49.
    When Machine Learning meets privacy - Episode 8
    29:21
  42. 50.
    Most Underrated MLOps Topics // Marian Ignev MLOps // Coffee Sessions #25
    54:08

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