Machine Learning with TensorFlow on Google Cloud Platform Specialization

开始时间: 02/15/2020 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: <

使用TensorFlow在Google Cloud Platform上进行机器学习专业化:什么是机器学习,它可以解决什么问题?将候选用例转换为机器学习驱动的五个阶段是什么?为什么不跳过这些阶段很重要?为什么神经网络现在如此流行?您如何设置有监督的学习问题,并使用梯度下降和周到的创建数据集的方法来找到一个好的通用解决方案?了解如何编写可在Tensorflow中扩展的分布式机器学习模型,并扩展对这些模型的培训。并提供高性能的预测。将原始数据转换为特征,使ML可以从数据中学习重要特征,并借助人类洞察力解决问题。最后,学习如何结合正确的参数组合,以产生准确,通用的模型和理论知识,以解决特定类型的ML问题。您将尝试端到端ML,从建立以ML为中心的策略开始,并逐步进行使用Google Cloud Platform进行动手实验的模型训练,优化和生产化。 &gt;通过注册此专业,您同意FAQ中列出的Qwiklabs服务条款,网址为:;


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