TensorFlow自动微分回归

Regression with Automatic Differentiation in TensorFlow

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Rhyme
Coursera
  • 完成时间大约为 1.5 个小时
  • 初级
  • 英语
注:本课程由Coursera和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

Understanding tensor constants, and tensor variables in TensorFlow.

Understanding automatic differentiation in TensorFlow.

Using automatic differentiation to solve a linear regression problem in TensorFlow.

课程概况

In this 1.5 hour long project-based course, you will learn about constants and variables in TensorFlow, you will learn how to use automatic differentiation, and you will apply automatic differentiation to solve a linear regression problem. By the end of this project, you will have a good understanding of how machine learning algorithms can be implemented in TensorFlow.

In order to be successful in this project, you should be familiar with Python, Gradient Descent, Linear Regression.

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

课程大纲

Regression with Automatic Differentiation in TensorFlow

Welcome to Regression with Automatic Differentiation in TensorFlow. In this project, we will get started with some of the important basics of TensorFlow - like tensor constants, variables, and automatic differentiation. We will then apply this knowledge to solve a linear regression problem. By the end of the project, you will have a good understanding on how to approach implementing machine learning algorithms in TensorFlow.

课程项目

Tensor Constants
Tensor Variables
Automatic Differentiation
Watching Tensors
Persistent Tape
Generating Data for Linear Regression
Linear Regression

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