Build a Deep Learning Based Image Classifier with R

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在此指導項目中,您將:

Solve a basic image classification problem with neural networks

Build, train, and evaluate a neural network model with Keras using R

Clock1 hour
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 45-min guided project, you will learn the basics of using the Keras interface to R with Tensorflow as its backend to solve an image classification problem. By the time you complete this project, you will have used the R programming language to build, train, and evaluate a neural network model to classify images of clothing items into categories such as t-shirts, trousers, and sneakers. We will be training the deep learning based image classification model on the Fashion MNIST dataset which contains 70000 grayscale images of clothes across 10 categories. In order to be successful in this project, you should be familiar with R programming, and basics of neural networks. 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.

您要培養的技能

  • Deep Learning
  • Artificial Neural Network
  • Machine Learning
  • Tensorflow
  • keras

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,您的授課教師將指導您完成每個步驟:

  1. Project Overview and Import Libraries

  2. Import the Fashion MNIST Dataset

  3. Data Exploration

  4. Preprocess the Data

  5. Build the Model

  6. Compile the Model

  7. Train and Evaluate the Model

  8. Make Predictions on Test Data

指導項目工作原理

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