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 QuickSight1m
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