IBM Watson Studio Enablement

Heba El-Shimy
IBM Cloud Developer Advocate
@heba_el_shimy
Github: HebaNAS

This repository will contain several demos covering different functionality available on IBM Watson Studio. Each demo will be enclosed in a separate folder along with its resources such as datasets and tutorial written as README.md.

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In these tutorials, we will learn how to:

1. Create a model and deploy it from a notebook in Watson Studio (02-CreditCardApprovalModel and 03-LoanApprovalModel).
2. Create a model using Watson Studio's Automatic Modeler (04-CreditCardApprovalWMLModeler).
3. Create a model using IBM SPSS Modeler ().
4. Create an Interactive Dashboard and share it (06-CustomerDemographicsDashboard).
5. Create an Image Classifier using Watson Visual Recognition (07-SignatureFraudDetectionVisualRecognition).
6. Create a Deep Learning Model using Watson Studio's Neural Network Modeler, adjusting model's hyperparameters and run experiments ().

Important Notes to follow along with this tutorial:

1. You'll need an IBM Cloud Account Sign up for IBM Cloud here: https://ibm.biz/WatsonStudioTutorials

Note: Whenever prompted to choose a country/location/region, choose United States/US-South.

2. Create an Object Storage instance by choosing it from the catalog.
   
   
   
   

3. Don't change any settings and click Create.
   
   
   
   

4. Congratulations! You've created the first Cloud Service Instance.
   
   
   
   

5. Create a Machine Learning instance by choosing it from the Watson category.
   
   
   
   

6. Don't change any settings and click Create.
   
   
   
   

7. Whenever you need to access your credentials for this service or any other, refer to the image below.
   
   
   
   

8. Create a Watson Studio instance by choosing it from Watson category.
   
   
   
   

9. Don't change any settings and click Create.
   
   
   
   

10. Click on Get Started to get redirected to Watson Studio Platform.
    
    
    
    

11. To start following the demos, you will need to create a New Project.
    
    
    
    

12. Select Complete to include all available tools into the project.
    
    
    

13. Type a name for your project and make sure the object storage is selected, then click Create.
    
    
    
    

14. Now let's start working on Data Science projects!