
Soheel Chughtai
IBM Early Experience Program Manager (eXp) - Watson Developer Cloud, IBM Systems
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.
This course is for developers who have little or no experience with machine learning. No data science background required. You must know how to work with Node-RED.
You need the following accounts:
Kaggle (to be able to download a data set of audio files)
Kaggle is dedicated to data science and machine learning and hosts data sets that can be used to generate machine learning models. The source audio files that you will use in this course is from Kaggle.
You need the following software:
IBM Early Experience Program Manager (eXp) - Watson Developer Cloud, IBM Systems
Emerging Technology Specialist, IBM Research
IBM Courseware Developer
No, but it's helpful if you understand object-oriented programming and have some experience with Node-RED.
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