Work with IBM's Watson Studio in this workshop to build, train, and test machine learning/deep learning models. Participants will be led through the following four hands-on labs. Note, the first lab is a prerequisite for the other labs. Once Lab-1 is completed, the other labs can be done in any order.
- Lab-1 - The first lab will set up the environment for the subsequent labs.
- Lab-2 - The second lab will use a Jupyter Notebook and the XGBoost library to apply machine learning to a classification problem in the healthcare profession. The Watson Machine Learning API will then be used to save and deploy the model.
- Lab-3 - The third lab will demonstrate Watson Machine Learning capabilites to simplify the building and deployment of machine learning models. The ability to monitor and adjust the deployed model will be demonstrated via the continuous learning capability of Watson Studio.
- Lab-4 - The fourth lab will feature the Watson Studio Neural Network modeler, and Experiment Assistant to build, train, and test a Convolutional Neural Network to classify images of handwritten digits.