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机器学习

Project: Simple Recurrent Neural Network with Keras

提供方
Rhyme
在此指導項目中，您將：

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.

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語（English）
Laptop僅限桌面

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.

您要培養的技能

Data ScienceMachine LearningTensorflowsequence modelsRecurrent Neural Network

分步進行學習

在與您的工作區一起在分屏中播放的視頻中，您的講師將指導您完成每個步驟：

  1. Introduction

  2. Generate Data

  3. Create the Model

  4. Vectorize and Devectorize data

  5. Create Dataset

  6. Training the Model

指導項目工作原理

Your workspace is a cloud desktop right in your browser, no download required

在分屏視頻中，您的講師會為您提供分步指導

講師

常見問題

常見問題

  • 購買指導項目後，您將獲得完成指導項目所需的一切，包括通過Web 瀏覽器訪問云桌面工作空間，工作空間中包含您需要了解的文件和軟件，以及特定領域的專家提供的分步視頻說明。

  • 由於您的工作空間包含適合筆記本電腦或台式計算機使用的雲桌面，因此指導項目不在移動設備上提供。

  • 指導項目講師是特定領域的專家，他們在項目的技能、工具或領域方面經驗豐富，並且熱衷於分享自己的知識以影響全球數百萬的學生。

  • 您可以從指導項目中下載並保留您創建的任何文件。為此，您可以在訪問云桌面時使用‘文件瀏覽器’功能。

  • 指導項目不提供助學金。

  • 指導項目不支持旁聽。

  • 您可在頁面頂部點按此指導項目的經驗級別，查看任何知識先決條件。對於指導項目的每個級別，您的講師會逐步為您提供指導。

  • 是，您可以在瀏覽器的雲桌面中獲得完成指導項目所需的一切。

  • 您可以直接在瀏覽器中於分屏環境下完成任務，以此從做中學。在屏幕的左側，您將在工作空間中完成任務。在屏幕的右側，您將看到有講師逐步指導您完成項目。

還有其他問題嗎？請訪問 學生幫助中心。