Data-centric AI development

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Destrezas que aprenderás

Human-level Performance (HLP), Concept Drift, Model baseline, Project Scoping and Design, ML Deployment Challenges

Reseñas

4.8 (2,050 calificaciones)

  • 5 stars
    84,87 %
  • 4 stars
    12,63 %
  • 3 stars
    1,75 %
  • 2 stars
    0,53 %
  • 1 star
    0,19 %

IU

5 de dic. de 2021

I have been involved with deep learning for more than 5 years (in academia), nevertheless learned a lot already. I am very curious about the next courses. Thanks for putting together this course!

EE

19 de may. de 2021

Excellent course, as always! Many thanks!

Great combination of theory + notebooks with practical examples.

Everything is perfectly structured. I will recommend this course to everyone!

De la lección

Week 2: Select and Train a Model

This week is about model strategies and key challenges in model development. It covers error analysis and strategies to work with different data types. It also addresses how to cope with class imbalance and highly skewed data sets.

Impartido por:

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    Andrew Ng

    Instructor

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    Cristian Bartolomé Arámburu

    Curriculum Developer

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