One of the most important aspects of Machine Learning is using the right data in the right format for your models. In this course you will learn how to extract, normalize, and select the best features for your models using Azure Machine Learning Studio.
It is no secret that Data Scientists spend a very large proportion of their time preparing data. In this course, Feature Selection and Extraction in Microsoft Azure, you'll gain the ability to prepare your data for use in your machine learning models. First, you'll learn how to extract features from raw data, including non-text formats. Next, you'll discover how to normalize features, converting your data to a common scale without distorting your data. Finally, you'll explore how to select those features that are more relevant to your model. When you're finished with this course, you'll have the skills and knowledge of feature extraction, normalization, and selection needed to prepare your data. Software required: Azure ML Studio classic.
Xavier is very passionate about teaching, helping others understand search and Big Data. He is also an entrepreneur, project manager, technical author, trainer, and holds a few certifications with Cloudera, Microsoft, and the Scrum Alliance, along with being a Microsoft MVP.
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