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Coursera How Google does Machine Learning

Google Cloud via Coursera

  • Overview
  1. Coursera
    Platform:
    Coursera
    Provider:
    Google Cloud
    Length:
    1 week
    Effort:
    8 to 10 hours per week
    Language:
    English
    Credentials:
    Paid Certificate Available
    Part of:
    Machine Learning with TensorFlow on Google Cloud Platform Specialization
    Overview
    >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: Terms of Service | Qwiklabs <<<

    What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently -- of being about logic, rather than just data. We talk about why such a framing is useful for data scientists when thinking about building a pipeline of machine learning models.

    Then, we discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important the phases not be skipped. We end with a recognition of the biases that machine learning can amplify and how to recognize this.

    Syllabus
    Introduction to specialization
    Introduces the specialization and the Google experts who will be teaching it.

    What it means to be AI first
    You will learn what we mean when we say that Google’s company strategy is to be AI-first, and what that means in practice.

    How Google does ML
    This module is about the organizational know-how Google has acquired over the years.

    Inclusive ML
    This module will discuss why machine learning systems aren’t fair by default and some of the things you have to keep in mind as you infuse ML into your products.

    Python notebooks in the cloud
    This module covers Cloud Datalab, which is the development environment you will use in this specialization.

    Summary

    Taught by
    Google Cloud Training

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