IBM Proof of Technology - Introduction to Data Science using Watson Studio

Description:

Watson Studio provides you with the environment and tools to solve your business problems by collaboratively working with data. You can choose the tools you need to analyze and visualize data, to cleanse and shape data, to ingest streaming data, or to create, train, and deploy machine learning/deep learning models. Watson Studio contains both open source and IBM value-add capabilities to help infuse AI into business to drive innovation.

Watson Studio is tightly integrated with the Watson Knowledge Catalog. The Watson Knowledge Catalog is a secure enterprise catalog to discover, catalog and govern your data/models with greater efficiency. The catalog is underpinned by a central repository of metadata describing all the information managed by the platform. Users will be able to share data with their colleagues more easily, regardless of what the data is, where it is stored, or how they intend to use it. In this way, the intelligent asset catalog will unlock the value held within that data across user groups—helping organizations use this key asset to its full potential.

The labs in this workshop will illustrate the myriad features included in Watson Studio, and Watson Knowlege Catalog. lab-1, Lab-2, and Lab-3 need to be completed in order. Subsequent labs are independent.

1. Lab-1 - The first lab will demonstrate the features of the Watson Knowledge Catalog

2. Lab-2 - The second lab will leverage Spark machine learning (SparkML) in a Jupyter notebook to create categorical predictions using pyspark and a supervised learning model. The model will be saved into a model repository using Watson Machine Learning APIs.

3. Lab-3 - The third lab will guide participants in examining an R notebook and Shiny UI in Watson Studio using RStudio. It will rely on the output results from Lab-1 and Lab-2.

4. Lab-4 - Neural Network Lab

5. Lab-5 - SPSS Modeler Lab

6. Lab-6 - Data Refinery Lab

7. Lab-7 - Visual Recognition Lab

8. Lab-8 - Natural Language Classifier Lab

Instructions: Create a Watson Studio project and set up the required services.

Step 1. Log into your Watson Studio account at datascience.ibm.com, then click on the hamburger icon, then Projects, and then View All Projects

Step 2. If you have an existing project from following the signup instructions then select it, and skip to Step 8. Otherwise, click on New Project.

Step 3. Hover the mouse over Standard, and click on Create Project.

Step 3. Enter the project name (eg. Watson Studio Labs), optionally a description, and then click on Add in the Storage section. Note if you have already provisioned cloud object storage (you shouldn't see an Add button) , then just click on the Create button, and skip to Step 8.

Step 4. Click on the Lite plan, and then click on Create.

Step 5. Optionally change the storage name, and then click on Confirm

Step 6. Click on Refresh.

Step 7. The cloud object storage should appear. Now click on Create.

Step 9. Click on the project Settings tab.

Step 10. Scroll down to Associated Services, then select Add service and select Watson.

Step 11. Select the Machine Learning service

Step 12. Select New.

Step 13. Select the Lite plan.

Step 13. Scroll down and click Create, then change the Service name to Machine Learning in the Confirm Creation panel and click Confirm.

Step 14. The Machine Learning service that you created should now appear in Associated Services.