Keras的简单递归神经网络

Simple Recurrent Neural Network with Keras

680 次查看
Rhyme
Coursera
  • 完成时间大约为 2 个小时
  • 普通(中级)
  • 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

Create, train, and evaluate a recurrent neural network (RNN) in Keras.

Train a sequence to sequence RNN model to be able to solve simple addition equations given in string format.

课程概况

In this hands-on project, you will use Keras with TensorFlow as its backend to create a recurrent neural network model and train it to learn to perform addition of simple equations given in string format. You will learn to create synthetic data for this problem as well. By the end of this 2-hour long project, you will have created, trained, and evaluated a sequence to sequence RNN model in Keras. Computers are already pretty good at math, so this may seem like a trivial problem, but it’s not! We will give the model string data rather than numeric data to work with. This means that the model needs to infer the meaning of various characters from a sequence of text input and then learn addition from the given data.

This course runs on Coursera’s hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed.

Notes:
– You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.
– 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

Simple Recurrent Neural Network with Keras

Welcome to this project-based course on creating and training a simple recurrent neural network using Keras and TensorFlow. In this project, you will use Keras with TensorFlow as its backend to create a recurrent neural network model and train it to learn to perform addition of simple equations given in string format. You will learn to create synthetic data for this problem as well. By the end of this 2-hour long project, you will have created, trained, and evaluated a sequence to sequence RNN model in Keras. Computers are already pretty good at math, so this may seem like a trivial problem, but it’s not! The interesting part here is that we will give the model string data and not numeric data to work with. This means that the model needs to infer the meaning of various characters from a sequence of text input and then learn addition from the given data!

课程项目

Introduction

Generate Data

Create the Model

Vectorize and Devectorize data

Create Dataset

Training the Model

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