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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.
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. Please note that you will need some experience in Python programming, and a theoretical understanding of Neural Networks to be able to finish this project successfully. 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.
Data Science
Machine Learning
Tensorflow
sequence models
Recurrent Neural Network
在与您的工作区一起在分屏中播放的视频中，您的授课教师将指导您完成每个步骤：
Introduction
Generate Data
Create the Model
Vectorize and Devectorize data
Create Dataset
Training the Model
您的工作空间就是浏览器中的云桌面，无需下载
在分屏视频中，您的授课教师会为您提供分步指导
由 DR 提供
Jul 12, 2020Good guided course. I would add a quite more deep details in the model architecture to understand better how are the inputs and the outputs of each layer in the RNN model
由 P 提供
May 21, 2020Best Understanding of Recurrent Neural Network in simplest way.
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指导项目授课教师是特定领域的专家，他们在项目的技能、工具或领域方面经验丰富，并且热衷于分享自己的知识以影响全球数百万的学生。
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是，您可以在浏览器的云桌面中获得完成指导项目所需的一切。
您可以直接在浏览器中于分屏环境下完成任务，以此从做中学。在屏幕的左侧，您将在工作空间中完成任务。在屏幕的右侧，您将看到有授课教师逐步指导您完成项目。
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