A hand holding a compass to symbolize data exploration

Exploratory Data Analysis

In this domain the data is analysed so it can be understood and cleaned up. It comprises 24% of the exam marks. Domain 2 is Exploratory Data Analysis, there are three subdomains:

Analysing and visualising the data (subdomain 2.3) overlaps with the other two sub-domains which use these techniques. The techniques include graphs, charts and matrices. Before data can be sanitized and prepared (subdomain 2.1) it has to be understood. This is done using statistics that focus on specific aspects of the data and graphs and charts that allow relationships and distributions to be seen. The data can then be cleaned using techniques to remove distortions and fill in gaps. Feature Engineering (subdomain 2.2) is about creating new features from existing ones to make the ML algorithms more powerful. Techniques are used to reduce the number of features and categorise the data.

When the data is understood and has been cleaned it is ready for the next stage, modeling.


Contains affiliate links. If you go to Whizlab’s website and make a purchase I may receive a small payment. The purchase price to you will be unchanged. Thank you for your support.

Whizlabs AWS Certified Machine Learning Specialty

Practice Exams with 271 questions, Video Lectures and Hands-on Labs from Whizlabs

Whizlab’s AWS Certified Machine Learning Specialty Practice tests are designed by experts to simulate the real exam scenario. The questions are based on the exam syllabus outlined by official documentation. These practice tests are provided to the candidates to gain more confidence in exam preparation and self-evaluate them against the exam content.

Practice test content

  • Free Practice test – 15 questions
  • Practice test 1 – 65 questions
  • Practice test 2 – 65 questions
  • Practice test 3 – 65 questions
Whizlabs AWS certified machine learning course with a robot hand

Section test content

  • Core ML Concepts – 10 questions
  • Data Engineering – 11 questions
  • Exploratory Data Analysis – 13 questions
  • Modeling – 15 questions
  • Machine Learning Implementation and Operations – 12 questions

Sample Exploratory Data Analysis questions

This test is five questions randomly taken from the questions in the tests of the three subdomains.

16

2 Exploratory Data Analysis

Five questions from a test bank of 30 questions about domain 2, Exploratory Data Analysis.

1 / 5

2 / 5

3 / 5

Why are numeric data in text fields converted to numeric data types?

4 / 5

What types of workforce can be used with Ground Truth?

5 / 5

The number of variables displayed in a bar chart is <–number–>

Study guides for exploratory data analysis

Two gloved hands holding a antibacterial hand sanitizer gel dispenser symbolising data cleansing
Exploratory Data Analysis (Domain 2)

Data cleansing and preparation for modeling

Understanding data, cleansing data and dataset generation are important first steps in exploratory data analysis. Every other phase in the Machine Learning process relies on the data being cleaned and prepared. This Study Guide starts with statistical techniques used to help understand the data. Once data is understood it has to be cleaned up so…

Whizlabs AWS certified machine learning course with a robot hand
Reviews

Whizlabs review – AWS Certified Machine Learning Specialty

Need more practice with the exams? Check out Whizlab’s free test with 15 questions. They also have three practice tests (65 questions each) and five section tests (10-15 questions each). Money off promo codes are below. For the AWS Certified Machine Learning Specialty Whizlabs provides a practice tests, a video course and hands-on labs. These…

Credits: Photo by Jamie Street on Unsplash