# Recognize-handwritten-digits-using-Neural-Networks-in-R

**Repository Path**: mirrors_ibm/Recognize-handwritten-digits-using-Neural-Networks-in-R

## Basic Information

- **Project Name**: Recognize-handwritten-digits-using-Neural-Networks-in-R
- **Description**: Create a web application to recognize handwritten digits using neural networks on R in Watson Studio
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-01-14
- **Last Updated**: 2025-11-23

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Recognize handwritten digits using Neural Networks in R

Interpreting images has been one of the most sought-after use cases in the field of artificial intelligence. Identification of handwritten digits using neural networks is commonly used in a lot of mobile applications.  

In this tutorial, we will learn how to create a Web Application to recognize handwritten digits using Neural Networks on R in Watson Studio. For this tutorial, we will be utilizing MNIST database which is the large database of handwritten digits commonly used in Machine Learning.

## Prerequisites
- An [IBM Cloud](https://cloud.ibm.com/registration/trial?utm_medium=OSocial&utm_source=Internal+Influencer&utm_content=000039JL&utm_term=10010797&utm_id=NA-Mostafa-Abdelaleem-T2-DigitRecognitionNeuralNetworkinRCodeProject-2021-10-31) account.
- [IBM Cloud Pak for Data](https://www.ibm.com/products/cloud-pak-for-data)
- A working knowledge of [R Programming Language](https://www.rstudio.com/)

## Estimated Runtime
It should take you approximately 45 minutes to complete this tutorial.

## Steps
[1. Create your IBM Cloud account and access IBM Cloud Pak for Data as a Service](#create-ibm-cloud-account-and-access-ibm-cloud-pak-for-data-as-a-service) </br>
[2. Create a new project](#create-a-new-project) </br>
[3. Launch RStudio Environment IDE](#launch-rstudio-environment-ide) </br>
[4. Add the files to your project](#add-the-files-to-your-project) </br>

## Create IBM Cloud account and access IBM Cloud Pak for Data as a Service
1. Sign in to [IBM Cloud](https://cloud.ibm.com/registration/trial?utm_medium=OSocial&utm_source=Internal+Influencer&utm_content=000039JL&utm_term=10010797&utm_id=NA-Mostafa-Abdelaleem-T2-DigitRecognitionNeuralNetworkinRCodeProject-2021-10-31).
2. Search for IBM Watson® Studio.
![](images/searchforcpd.png)
3. Create the service by selecting the region and pricing plan, then click **Create**.
![](images/createcpd.png)

## Create a new project
1. Start the Watson Studio service.
![](images/createaproject.png)
2. Click Create a project and Create an empty project. Make sure that you name your project and add a storage service, then click **Create**.
![](images/createanemptyproject.png)
![](images/defineprojectdetails.png)

## Launch RStudio Environment IDE
1. Go to **Assets** and click on **Launch IDE** and Select **RStudio**.
![](images/gotoassets.png)
![](images/selectRStudio.png)

2. Select **Default RStudio XS (2 vCPU and 8 GB RAM)** runtime and click on **Launch**.
![](images/RStudioenironmentsetup.png)
![](images/RStudioonWatsonStudio.png)

## Add the files to your project
1. Click on **New Folder** icon on under **Files** on the Right-hand side bottom.
![](images/createnewfolder.png)
2. Open the newly created folder and upload the zip folder of the GitHub Repository from the following URL. <br/>
`https://github.com/mridulrb/Recognize-handwritten-digits-using-Neural-Networks-in-R`
![](images/uploadfilestoRStudio.png)
![](images/uploadzipfolder.png)
3. Click on **More** and select **Set As Working Directory**.
![](images/setasworkingdirectory.png)
![](images/RConsole.png)
4. Double-click and open **neuralNetwork.R** file from the uploaded files by double-clicking on it. Click on **Run** and execute each line individually, wait for the arrow head to appear before clicking on **Run** to execute the next line.
![](images/NeuralNetwork.png)
![](images/NeuralNetworkRScriptrun.png)
![](images/NeuralNetworkRScriptconsole.png)
5. After training the Neural Network, we can now run the Web Application to recognize Handwritten Digits. Before that we need to install some packages. Enter the following commands in Console. <br/>
**Installing shiny package**
```
install.packages(“shiny”) 
```
**Installing nnet package**
```
install.packages(“nnet”) 
```
**Installing EBImage package**
```
install.packages(“BiocManager”) 
BiocManager::install(“EBImage”) 
```
Open the **DigitRecognizer.R** file from the uploaded files by double-clicking on it. Click on **Run App** to Run the Web Application. You can upload the sample images from the Sample-Images folder in the GitHub Repository downloaded earlier on your computer to test the Application.
![](images/DigitRecognizerWebApp.png)
![](images/DigitRecognizer.gif)
  

## Conclusion
In this tutorial, we learned how to create and visualize a neural network that takes in a dataset and trains a model to predict outcomes.