This is an introduction to Machine Learning using IBM Watson Studio suite of products. We will introduce the tooling followed by a demo of Classification and Regression. Watson Machine Learning empowers your cross-functional team to deploy, monitor and optimize models quickly and easily. Once a model is deployed, APIs are generated automatically to help developers infuse AI into their applications quickly.
We will demo end to end machine learning lifecycle in this demo
1. Gather data and store on IBM Cloud Storage.
2. Data wrangling and cleanup using IBM Refinery.
3. Use Watson Machine Learning to create several classification and regression models.
4. Ask Watson Studio to pick the best performing model for you.
5. Deploy the model and then create a web application for prediction.
6. Learn how to continuously evaluate this model and improve over time. Introduction to Machine Learning on IBM Watson Studio
Upkar Lidder is a Full Stack Developer and Data Wrangler with a decade of development experience in a variety of roles. He can be seen speaking at various conferences and participating in local tech groups and meetups. Upkar went to graduate school in Canada and currently resides in the United States