Feature Selection and Extraction in Microsoft Azure

Focused View

Xavier Morera

1:27:20

104 View

1. Course Overview

1. Course Overview.mp4

01:30

2. Exploring Your Dataset for Feature Selection and Extraction

1. Exploring Your Dataset for Feature Selection and Extraction.mp4

01:44

2. What Is a Feature in Machine Learning.mp4

04:21

3. Exploring Your Data and Identifying the Distribution of Your Da.mp4

04:40

4. Determining the Feature Structure Appropriate for the Algorithm.mp4

01:44

5. Dataset Exploration Demo.mp4

04:52

6. Takeaway.mp4

00:58

3. Performing Feature Extraction

1. What Is Feature Extraction.mp4

01:24

2. Performing Feature Extraction.mp4

07:38

3. Creating and Using Feature Extraction Algorithms.mp4

02:20

4. Performing Feature Extraction on Unstructured Text.mp4

05:57

5. Demo - Human Face or Not Human Face.mp4

05:34

6. Takeaway.mp4

00:35

4. Performing Feature Normalization

1. Performing Feature Normalization.mp4

01:07

2. Understanding Feature Normalization.mp4

02:06

3. Clip Values Demo.mp4

03:18

4. Group Data into Bins Demo.mp4

03:15

5. Normalize Data Demo.mp4

02:30

6. Principal Component Analysis Demo.mp4

02:45

7. Encoding Features Demo.mp4

03:59

8. Takeaway.mp4

00:59

5. Performing Feature Selection

1. Performing Feature Selection.mp4

01:52

2. Understanding Feature Selection.mp4

01:50

3. Fliter Based Feature Selection Demo.mp4

02:47

4. Fisher Linear Discriminant Analysis Demo.mp4

05:44

5. Permutation Feature Importance Demo.mp4

03:46

6. Compute Linear Correlation Demo.mp4

04:58

7. Takeaway.mp4

01:14

6. Final Takeaway

1. Final Takeaway.mp4

01:53

Description

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.

What You'll Learn?

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.

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Microsoft Azure

Xavier Morera

Instructor's Courses

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. He has spent a great deal of his career working on cutting-edge projects with a primary focus on .NET, Solr, and Hadoop among a few other interesting technologies. Throughout multiple projects, he has acquired skills to deal with complex enterprise software solutions, working with companies that range from startups to Microsoft. Xavier also worked as a worldwide v-trainer/evangelist for Microsoft.

Pluralsight

View courses Pluralsight

Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.