DataTalks.Club

Building Scalable and Reliable Machine Learning Systems - Arseny Kravchenko


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We talked about:

  • Arseny's background
  • Working on machine learning in startups
  • What is Machine Learning System Design?
  • Constraints and requirements
  • Known unknowns vs unknown unknowns (Design stage)
  • Writing a design document
  • Technical problems vs product-oriented problems
  • The solution part of the Design Document
  • What motivated Arseny to write a book on ML System Design
  • Examples of a Design Document in the book
  • The types of readers for ML System Design
  • Working with the co-author
  • Reacting to constraints and feedback when writing a book
  • Arseny's favorite chapter of the book
  • Other resources where you can learn about ML System Design
  • Twitter Giveaway

  • Links:

    • Book: https://www.manning.com/books/machine-learning-system-design?utm_source=AGMLBookcamp&utm_medium=affiliate&utm_campaign=book_babushkin_machine_4_25_23&utm_content=twitter
    • Discount: poddatatalks21 (35% off)

    • Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp

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