Exploratory Data Analysis with AWS Machine Learning

Description

In this course, you will :

• Explore how to use basic statistics to comprehend data trends and distribution.
• Learn how to visualise your dataset in order to understand the overall patterns.
• Learn how to do preprocessing and feature engineering to prepare your data for the machine learning pipeline.

Syllabus :

1. Machine Learning with AWS

• Refresher: AWS Machine Learning Pipeline
• About AWS Machine Learning Specialty Exam
• About the Course
• What Is Data Analysis?
• Introducing Our Dataset

 

2. Data Analysis Using AWS

• Globomantics Data Analysis Team
• Data in the Real World
• Naming Things Like a Pro
• Statistics Refresher
• Probability Refresher
• Skewness and Kurtosis

 

3. Data Visualization Using AWS

• Why Data Analysis?
• Usage of Data Analysis
• Box and Whisker Plot
• Types Of Visualizations
• AWS QuickSight

 

4. Data Preparation Using AWS

• Why Data Preparation?
• Imbalanced Data Challenge
• Scale of Features Challenge
• Inconsistent Formats Challenge
• Difficult Presentation of Data Challenge
• Missing Data Challenge
• Outliers Challenge
• High Dimensionality Challenge
• Highly Correlated Features Challenge
• Malformed Distribution Challenge

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