Reducing Complexity in Data in Microsoft Azure

In machine learning, feature sets can quickly become complicated and unwieldy. This course will give you the skills needed to reduce the complexity of your feature sets to help ensure you get better and more consistent insights into your data.
Course info
Level
Advanced
Updated
Dec 10, 2019
Duration
2h 14m
Table of contents
Description
Course info
Level
Advanced
Updated
Dec 10, 2019
Duration
2h 14m
Description

If you're building models for data science, your feature sets can quickly become complicated and hard to understand. In this course, Reducing Complexity in Data in Microsoft Azure, you will learn how to reduce the complexity of feature sets, making models more understandable, more straightforward to build, and more robust. First, you will learn to understand feature set complexity and how it impacts your models. Next, you will discover a range of different techniques to improve the complexity of your feature sets. Finally, you will explore various advanced methods for feature set complexity reduction. When you are finished with this course, you will have the skills and knowledge needed to reduce the complexity of your models, and create more straightforward and manageable models, leading to better and more consistent insights into your data.

About the author
About the author

Steph Locke is a data scientist, entrepreneur, and Microsoft MVP in AI and Data Platform.

Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi everyone. My name is Steph Locke, and welcome to my course, Reducing Complexity in Data in Microsoft Azure. I'm CEO of Nightingale HQ, and work as a data science consultant and trainer. I'm also a Microsoft AI and Data Platform MVP. In this course, we are going to learn the techniques needed to reduce feature set complexity for our data science models. Some of the major topics that we will cover include feature set complexity and how it impacts our models, how to handle numeric, categorical, and text features, and many techniques ranging from simple to complex to help us transform our feature sets into something more manageable. By the end of this course, you'll have the skills and knowledge needed to manage feature set complexity and create more straightforward and manageable models. This will lead to better and more consistent insights into your data. Before beginning this course, you should be familiar with Python and data science, at least at a high level. I hope you'll join me on this journey to get more out of your data, with the Reducing Complexity in Data in Microsoft Azure course, at Pluralsight.