Modeling overview

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Compétences que vous apprendrez

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

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4.8 (1,162 évaluations)

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    83,73 %
  • 4 stars
    13,25 %
  • 3 stars
    1,89 %
  • 2 stars
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  • 1 star
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AC

8 juin 2021

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I have been working in a large payments technology company for last one year and I can vouch for all the processes Andrew beautifully summarised. It does help a lot working in the industry.

UU

4 juin 2021

Filled StarFilled StarFilled StarFilled StarFilled Star

The content of this course has been especially useful for me. I wish there were more emphasis on the tools recommendation as well, but the theoretical knowledge was just fine. Thank you!

À partir de la leçon

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.

Enseigné par

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    Andrew Ng

    Instructor

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    Cristian Bartolomé Arámburu

    Curriculum Developer

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