HomeMachine Learning Tests
Pattern Recognition Skills Test
Test duration:
No. of questions:
Level of experience:
Entry Level/Mid/Senior

Pattern Recognition ML Skills Test

Recruiters and hiring managers can use this test to assess individuals’ skill proficiency in areas like recognizing patterns, making sense of complex data sets, and drawing accurate conclusions for machine learning roles. It can even reduce hiring time by 45% and create dedicated upskilling programs.

A blue triangle

What is Pattern Recognition?

It is a data analysis technique that uses various ML algorithms to recognize patterns in different datasets. This data can be anything from images and text to sounds or similar definable qualities.

Why use iMocha’s test?

This skill test can easily find candidates and employees with this important skill to make sense of large amounts of data and find relationships that are hard to see otherwise. Additionally, our role-based access control feature restricts system access based on the roles of individual users within the recruiting team.

Wondering what other skills we have in our World’s Largest Skills Assessment library?
Visit here
How it works

Test Summary

This skill test helps to screen employees & candidates who possess the below skill sets:

  • Expertise in Python, C++, R, Java, and GoLang.
  • Knowledge of statistical algorithm models that help analyze aspects such as the probability distribution, decision boundaries, etc., for the patterns.
  • Familiarity with NoSQL, SQL, relational, and graph data stores.
  • Experience and interest in using recognition techniques to analyze large data sets and images.
  • Knowledge of APIs, such as TensorFlow, Keras, or PyTorch.
  • Understanding related areas such as data mining, regression analysis, probability theory, and hypothesis testing.
  • Proficiency in various neural network architectures used in Deep Learning, Reinforcement Learning, Clustering, Principal component analysis (PCA), etc.
  • Experience in developing with OpenCV or similar toolkits.
Useful for hiring
  • Data Scientist
  • Machine Learning Engineer
  • Computer Vision Engineer
  • Natural Language Processing (NLP) Engineer
  • Business Intelligence Analyst
  • Quality Control Engineer
  • Operations Research Analyst
  • Data Analyst
  • Cybersecurity Analyst
  • Fraud Analyst
  • Quality Control Engineer
  • Operations Research Analyst
Test Duration
No. of Questions
Level of Expertise
Entry Level/Mid/Senior
Topics Covered





Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.
Question type
Topics covered


A helicopter view of the employee's progress
View Full Report
Test Report
You can customize this test by

Setting the difficulty level of the test

Choose easy, medium, or tricky questions from our skill libraries to assess candidates of different experience levels.

Combining multiple skills into one test

Add multiple skills in a single test to create an effective assessment and assess multiple skills together.

Adding your own
questions to the test

Add, edit, or bulk upload your coding, MCQ, and whiteboard questions.

Requesting a tailor-made test

Receive a tailored assessment created by our subject matter experts to ensure adequate screening.
How is this skill test customized?
Down Arrow Circle

Our SMEs can customize the test to the required primary and secondary abilities, such as Data Framework, Python, Supervised and Unsupervised Learning, and many more. Likewise, questions can be customized based on candidates' skill levels and experience.

What are the most common interview questions related to ml pattern recognition skills?
Down Arrow Circle

Some of the common questions asked for this role are:

  • What are the various steps of designing a system?
  • Explain statistical pattern recognition.
  • What is the difference between Data Mining and Machine Learning?
  • Differentiate supervised and unsupervised.
  • What are the different types of Algorithm methods in pattern recognition?
  • What are the functions of supervised and unsupervised learning?

If you are looking for a more custom set of questions, iMocha can help!