📊 IBM Cloud Pak for Data Tutorial: Part V

In this hands-on tutorial you will deploy a local Python app to test your model.

Prerequisites

1. Sign up for an IBM Cloud account.
2. Fill in the required information and press the „Create Account“ button.
3. After you submit your registration, you will receive an e-mail from the IBM Cloud team with details about your account. In this e-mail, you will need to click the link provided to confirm your registration.
4. Now you should be able to login to your new IBM Cloud account ;-)
5. Make sure to download Python

IBM Cloud Pak for Data Tutorials Part I to VI

This tutorial consists of 6 parts, you can start with part I or any other part, however, the necessary environment is set up in part I.
Part I - data visualization, preparation, and transformation
Part II - build and evaluate machine learning models by using AutoAI
Part III - graphically build and evaluate machine learning models by using SPSS Modeler flow
Part IV - set up and run Jupyter Notebooks to develop a machine learning model
Part V - deploy a local Python app to test your model
Part VI - monitor your model with OpenScale

The first 4 parts of this tutorial are based on the Learning path: Getting started with Watson Studio.

1) CRISP-DM

The CRoss Industry Standard Process for Data Mining is a model to display the cycle of a data science project. It consists of six phases:
1. Business Understanding - What does the business need?
2. Data Understanding - What data do we have and how is it made up of?
3. Data Preparation - How can we structure the data for the modeling?
4. Modeling - Which modeling techniques could apply?
5. Evaluation - Which model is the most accurate?
6. Deployment - How to implement the model?

In this case we only focus on the deployment of the model.

Start the app

• Download the repository to start the app on your local machine

• Open .env.example, rename it to .env and enter your API-Key, URL, Space-ID and Deployment-ID, then save the file

  • If you don't have one already create a new API-Key here or check out the previous Tutorial.
  • The default url for wml services in the US is https://us-south.ml.cloud.ibm.com
  • Find your Space-ID in your IBM Cloud Pak for Data --> Deployment Spaces --> Your Deployment Space --> Manage --> Space GUID (alternatively you can also find it in the URL)
  • Find your Deployment-ID in your IBM Cloud Pak for Data --> Deployment Spaces --> Your Deployment Space --> Deployments --> Your Deployment --> Info Panel on the right hand side

• Start a terminal at the folder that contains the file app.py, in this case the folder is cloud-pak-for-data-tutorial-part-v-master

• You might have to install IBM Watson ML with the following commands: pip install ibm_watson-machine-learning

• You might also have to install flask, python-dotenv and python-decouple with the following commands: pip install flask or pip install -U Flask , pip install python-dotenv and pip install python-decouple

• Then start the app by typing: python app.py or if you are using python3 python3 app.py

• Insert some values and hit the predict button