Machine LearningSkill Test
Covered Skills
- Unsupervised learning, outlier detection, and dimensionality reduction
- Tree-based and ensemble methods for regression and classification
- Classical classification methods and support vector machines
- Classical regression methods and regularization
Test CategoryRole specific skills
Total Time15:00
Test LevelIntermediate
DescriptionIn our age of information and technology, businesses across industries have to deal with massive amounts of data. It is crucial to leverage this data to obtain insights that can drive decision-making. Harnessing the power of machine learning can help your business to more easily adapt to ever-changing market conditions, improve business operations, and gain a deeper understanding of consumer needs.
This machine learning test evaluates candidates’ knowledge of the fundamental concepts in machine learning, including both classical and tree-based ensemble methods for regression and classification, supervised and unsupervised learning, outlier detection, and dimensionality reduction. The questions on this machine learning test focus on different scenarios when working with data, covering the different ML functionalities for dealing with each of them.
Candidates who perform well on the test have a strong knowledge of core machine learning approaches and can make the best use of these approaches when working with different types of information. They have all the necessary skills to help your business harness machine learning to power data-driven decision-making.
Relevant Job RolesMachine learning engineers, data engineers, data analysts, data visualization creators, artificial intelligence engineers, entrepreneurs, decision makers, and any other roles requiring intermediate knowledge of Machine Learning.
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