Machine Learning with TensorFlow on Google Cloud Platform 专项课程

开始日期 Aug 13

Machine Learning with TensorFlow on Google Cloud Platform 专项课程

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

本专项课程介绍

>>> 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 <<< ***Google Cloud and Kaggle would like to invite you to join our New York City Taxi Fare Prediction Playground Competition happening now! For details, please visit: https://www.kaggle.com/c/new-york-city-taxi-fare-prediction*** 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.

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5 courses

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项目概览

课程
Intermediate Specialization.
Some related experience required.
  1. 第 1 门课程

    How Google does Machine Learning

    当前班次:Aug 13
    课程学习时间
    1 week of study, 8-10 hours/week
    字幕
    English, Portuguese (Brazilian)

    课程概述

    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 when thinking about building a pipeli
  2. 第 2 门课程

    Launching into Machine Learning

    当前班次:Aug 13
    字幕
    English

    课程概述

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

    Intro to TensorFlow

    计划开课班次:Aug 20
    课程学习时间
    1 week of study, 8-10 hours/week
    字幕
    English

    课程概述

    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 门课程

    Feature Engineering

    计划开课班次:Aug 20
    课程学习时间
    2 weeks of study, 5-7 hours per week
    字幕
    English

    课程概述

    Want to know how you can improve the accuracy of your machine learning models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering on Google Cloud Platform where we will discuss the elements of good v
  5. 第 5 门课程

    Art and Science of Machine Learning

    当前班次:Aug 13
    课程学习时间
    3 weeks of study, 5-7 hours per week
    字幕
    English

    课程概述

    Welcome to the art and science of machine learning. In this 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 will lear

制作方

  • 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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