mlops
Ctrlk
  • MLops
  • MLops
    • Chap 0. Before everything
    • Chap 1. Tools for developers
    • Chap 2. Hardware
    • Chap 3. Infrastructure/platform design
    • Chap 4. Toolkit/codebase
    • Chap 5. Paper reproduction
    • Chap 6. Prototype development
    • Chap 7. Deployment and model serving
    • Chap 8. Productionization/Maintenance/Adoption
    • Chap 9. PR/keep stoa
      • 9.0 Conference
      • 9.1 Challenges/Competitions
      • 9.2 Lectures/Webinars
      • 9.3 Tech blogs
        • Notes on machine learning in product
        • work at data science group in linkedin
        • What skillsets should a full-stack ML engineer have
        • What it takes to be a ML infra engineer
        • Google engineer tool
        • Infra at Netflix
        • Infra notes
      • 9.4 open sources wheels
    • Acknowledge
  • DataOps
    • Chap 0. Preface
    • Chap 1. Data engineering
    • Chap 2. Data integration
    • Chap 3. Data security/privacy
    • Chap 4. Data quality
  • MODELOPS
    • Chap 0. Intro
    • Chap 1. Model registery
  • Fun Facts about Image
    • Chap 0. Preface
    • Chap 1. Process
    • Chap 2. Metrics
    • Chap 3. Case Study
  • Softskills
    • Chap 1. Mindsets
    • Chap 2. Soft skills in getting things done
    • Chap 3. Portfolio and side projects
    • Chap 4. Mentorship
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  1. MLops
  2. Chap 9. PR/keep stoa
  3. 9.3 Tech blogs

Infra notes

https://github.com/DA-southampton/Tech_Aarticle

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Last updated 4 years ago

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