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Coursera Project Network

Build a Deep Learning Based Image Classifier with R

Coursera Project Network via Coursera

Overview

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.

Syllabus

  • Build a Deep Learning Based Image Classifier with R
    • 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.

Taught by

Snehan Kekre

Reviews

4.6 rating at Coursera based on 175 ratings

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