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.
Course Overview Hi everyone. My name is Xavier Morera, and welcome to my course, Feature Selection and Extraction in Microsoft Azure. I am very passionate about working with data, and data, particularly large amounts of data, being a cornerstone of machine learning. There is no doubt in my mind that machine learning is the future, and you know what makes machine learning easier? Well, Azure ML Studio. In this course, we're going to learn how to perform one of the most basic and necessary steps of preparing our data for machine learning, what's called feature extraction and selection, with the help of Azure ML Studio. Some of the major topics that we will cover include feature extraction, feature normalization, and feature selection. By the end of this course, you will be able to extract, normalize, and select features from different types of datasets, be it from text, numerical data, images or other sources with the help of Azure Ml Studio. Before beginning the course, you should be familiar with the basic concepts of machine learning, as well as Microsoft Azure. I hope you'll join me on this journey to learn how to extract, normalize, and select features with the Feature Selection and Extraction in Microsoft Azure course, at Pluralsight.