Machine Learning with TensorFlow on Google Cloud Platform Specialization

开始时间: 09/14/2019 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



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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. > By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: <


How Google does Machine Learning
Launching into Machine Learning
Intro to TensorFlow
Feature Engineering





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


Tensorflow 机器学习 深度学习 Google Google云平台