Machine Learning with TensorFlow on Google Cloud Platform Specialization

开始时间: 11/17/2018 持续时间: Unknown

所在平台: Coursera专项课程

课程类别: 计算机科学

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/specializations/machine-learning-tensorflow-gcp

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课程详情

>>> 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? 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.

课程大纲

5 courses

How Google does Machine Learning

>>> 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

Launching into Machine Learning

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 desce

Intro to TensorFlow

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-per

Feature Engineering

>>> 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 fi

Art and Science of Machine Learning

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

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课程简介

谷歌云平台上的TensorFlow机器学习专项课程系列(Machine Learning with TensorFlow on Google Cloud Platform Specialization),这个系列包含5门子课程,涵盖Google如何做机器学习,机器学习介绍及启动,TensorFlow导引,特征工程,机器学习中的艺术和科学,感兴趣的同学可以关注

课程标签

Tensorflow 机器学习 深度学习 Google Google云平台

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