Get hands-on experience creating and training machine learning models so that you can predict what animal is making a specific sound, like a cat purring or a dog barking. Integrate those models in a simple web page that you build in Node-RED. Then, add visual recognition so that you can identify the image of an animal.

If you’re a developer and want to learn about machine learning, this is the course for you. Even if you have some experience with machine learning, you might not have worked with audio files as your source data. Either way, you’ve come to right place. In this course, you’ll learn to create basic machine learning models that you train to recognize the sounds of dogs, cats, and birds. You’ll also integrate visual recognition to identify images of these animals. You’ll build a basic user interface in Node-RED that shows the results of the predictions for both sound and images. You’ll use IBM Watson Studio to build classification models to predict and identify animal sounds and use IBM Watson Visual Recognition to identify images of those animals. You’ll learn how best to gather and prepare data, create and deploy models, deploy and test a signal processing application, create models with binary and multiclass classifications, and display the predictions on a web page.