Exploratory Data Analysis with AWS Machine Learning

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Mohammed Osman

2:16:37

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01. Course Overview

01. Course Overview.mp4

02:00

02. Machine Learning with AWS

01. Overview.mp4

01:21

02. Refresher AWS Machine Learning Pipeline.mp4

06:05

03. About AWS Machine Learning Specialty Exam.mp4

02:14

04. About the Course.mp4

01:30

05. What Is Data Analysis.mp4

04:02

06. Introducing Our Dataset.mp4

00:56

07. Demo. Setting up the Environment.mp4

05:37

08. Summary.mp4

01:56

03. Data Analysis Using AWS

01. Overview.mp4

02:02

02. Globomantics Data Analysis Team.mp4

02:59

03. Data in the Real World.mp4

02:56

04. Naming Things Like a Pro.mp4

02:09

05. Statistics Refresher.mp4

06:21

06. Probability Refresher.mp4

04:19

07. Skewness and Kurtosis.mp4

05:25

08. Demo. Data Analysis Using AWS.mp4

07:12

09. Summary.mp4

02:24

04. Data Visualization Using AWS

01. Overview.mp4

01:23

02. Why Data Analysis.mp4

01:17

03. Usage of Data Analysis.mp4

00:35

04. Box and Whisker Plot.mp4

01:16

05. Types Of Visualizations.mp4

06:20

06. Demo. AWS SageMaker Visualization.mp4

06:22

07. AWS QuickSight.mp4

00:40

08. Demo. Amazon QuickSight.mp4

04:53

09. Summary.mp4

01:30

05. Data Preparation Using AWS

01. Overview.mp4

00:39

02. Why Data Preparation.mp4

04:01

03. Imbalanced Data Challenge.mp4

02:39

04. Scale of Features Challenge.mp4

02:52

05. Inconsistent Formats Challenge.mp4

02:37

06. Difficult Presentation of Data Challenge.mp4

01:54

07. Missing Data Challenge.mp4

02:17

08. Outliers Challenge.mp4

03:25

09. High Dimensionality Challenge.mp4

04:21

10. Highly Correlated Features Challenge.mp4

04:20

11. Malformed Distribution Challenge.mp4

03:07

12. Demo. Fixing Missing Values.mp4

09:23

13. Demo. Removing Highly Correlated Features.mp4

02:05

14. Demo. Removing Outliers.mp4

01:06

15. Demo. Fixing Difficult Presentation of Data.mp4

01:08

16. Demo. Fixing Scale of Data.mp4

01:01

17. Demo. Fixing Malformed Distribution.mp4

00:51

18. Summary.mp4

03:07

Description

Understanding how to deal with data is becoming a required skill in the information age. This course will teach you how to do exploratory data analysis and leverage relevant AWS services.

What You'll Learn?

Understanding underlying trends and outliers in data is a necessary step to do proper data preparation and feature engineering for subsequent machine learning tasks.

In this course, Exploratory Data Analysis with AWS Machine Learning, you’ll learn how to analyze, visualize, preprocess and feature engineer datasets to make them ready for subsequent machine learning steps.

What you will learn in this beginner level AWS machine learning tutorial:

First, you’ll explore how to understand data trends and distribution using basic statistics.
Next, you’ll discover how to visualize your dataset to understand the overall patterns.
Finally, you’ll learn how to prepare your data for the machine learning pipeline by doing preprocessing and feature engineering.

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Machine Learning

Data Science

Amazon AWS

Mohammed Osman

Instructor's Courses

Mohammed Osman is a senior software engineer who started coding at the age of 13. Mohammed worked in various industries, including telecommunication, accounting, banking, health, and assurance. Mohammed's core skillset is a .NET ecosystem with a strong focus on C#, Azure, and Data Science. Mohammed also enjoys the soft-side of software engineering and leads scrum teams. Mohammed runs a blog with the message "Making your code smart and your career smarter." He shares tips and techniques to improve your code and valuable career pieces of advice in his blog.

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.