World Model · podcast knowledge graph

EP 7: Data Science & MLOps

2022-12-27 · 39 min · episode 7 · 9 entities

episode page audio

Asserted relationships

  • → hosted by Soumava Dey person
    0.55
    evidence rules-v5
    Feed author/publisher: Soumava Dey
  • → discusses Technology company
    0.40
    evidence rules-v5
    Feed category: Technology
  • → references Articles website
    0.38
    evidence rules-v5
    Link in episode "EP 7: Data Science & MLOps": https://martinfowler.com/articles/dat
  • → references ml-ops.org website
    0.38
    evidence rules-v5
    Link in episode "EP 7: Data Science & MLOps": https://ml-ops.org/

Entities found in this episode

websites 4

  • mentioned Articles website
    0.45
    evidence rules-v5
    Link in episode "EP 7: Data Science & MLOps": https://martinfowler.com/articles/dat
  • mentioned ml-ops.org website
    0.45
    evidence rules-v5
    Link in episode "EP 7: Data Science & MLOps": https://ml-ops.org/
  • references Articles website
    0.38
    evidence rules-v5
    Link in episode "EP 7: Data Science & MLOps": https://martinfowler.com/articles/dat
  • references ml-ops.org website
    0.38
    evidence rules-v5
    Link in episode "EP 7: Data Science & MLOps": https://ml-ops.org/

persons 2

  • mentioned Soumava Dey person
    0.70
    evidence rules-v5
    Feed author/publisher: Soumava Dey
  • hosted by Soumava Dey person
    0.55
    evidence rules-v5
    Feed author/publisher: Soumava Dey

companys 2

  • mentioned Technology company
    0.50
    evidence rules-v5
    Feed category: Technology
  • discusses Technology company
    0.40
    evidence rules-v5
    Feed category: Technology

concepts 1

Episode description as stored
Latest coffee chat session on Data Science features Aaron Blythe, Data Scientist and Solution Architect at Google. During this discussion, Aaron talked about various topics such as 1) essential toolkit to become a Data Scientist, 2) fundamental difference between a Data Scientist and a ML Engineers and how they can work in collaborative environment to develop sophisticated pipeline for model deployment? 3) significance of MLOps practice to modernize the Data Science model deployment pipeline by bringing CI/CD culture in Data Science world. Important learning materials: https://martinfowler.com/articles/dat ... https://ml-ops.org/ Share your questions/comments below. Today's guest speaker Aaron can be reached at https://www.linkedin.com/in/aaronblythe/