Machine Learning with TensorFlow on Google Cloud Platform 專項課程

於 Nov 15 開始

Machine Learning with TensorFlow on Google Cloud Platform 專項課程

Learn ML with Google Cloud。 Real-world experimentation with end-to-end ML.

本專項課程介紹

> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service < *Look for details below for COMPLETION CHALLENGE, receive a GCP t-shirt!* What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets? Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem. Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems. You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform. Complete any GCP specialization from now through November 30, 2018 for an opportunity to receive a GCP t-shirt (while supplies last). See forums for details.

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5 courses

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項目概覽

課程
Intermediate Specialization.
Some related experience required.
  1. 第 1 門課程

    How Google does Machine Learning

    課程學習時間
    1 week of study, 8-10 hours/week
    字幕
    英語(English), 法語(French), 巴西葡萄牙語, 德語(German), 西班牙語(Spanish), 日語

    課程概述

    >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<< What is machine learning, and what kinds of problems can it solve? Google thinks about ma
  2. 第 2 門課程

    Launching into Machine Learning

    課程學習時間
    5 - 7 hours per week
    字幕
    英語(English), 法語(French), 巴西葡萄牙語, 德語(German), 西班牙語(Spanish), 日語

    課程概述

    Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of data science problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent.
  3. 第 3 門課程

    Intro to TensorFlow

    課程學習時間
    1 week of study, 8-10 hours/week
    字幕
    英語(English), 法語(French), 巴西葡萄牙語, 德語(German), 西班牙語(Spanish), 日語

    課程概述

    We introduce low-level TensorFlow and work our way through the necessary concepts and APIs so as to be able to write distributed machine learning models. Given a TensorFlow model, we explain how to scale out the training of that model and offer high-perfor
  4. 第 4 門課程

    Feature Engineering

    課程學習時間
    2 weeks of study, 5-7 hours per week
    字幕
    英語(English), 法語(French), 巴西葡萄牙語, 德語(German), 西班牙語(Spanish), 日語

    課程概述

    >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<< Want to know how you can improve the accuracy of your machine learning models? What about how to find
  5. 第 5 門課程

    Art and Science of Machine Learning

    課程學習時間
    3 weeks of study, 5-7 hours per week
    字幕
    英語(English), 巴西葡萄牙語, 德語(German), 西班牙語(Spanish), 日語

    課程概述

    Welcome to the art and science of machine learning. In this data science course you will learn the essential skills of ML intuition, good judgment and experimentation to finely tune and optimize your ML models for the best performance. In this course you

製作方

  • Google Cloud

    The Google Cloud training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an effective and impactful way.

    We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

  • Google Cloud Training

    Google Cloud Training

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