Machine Learning Assessment to Evaluated Machine Learning Skills

About This Assessment

This Machine Learning assessment aims to measure work readiness skills in core and advanced concepts of the Machine Learning algorithm. Along with assessing domain knowledge, this Machine Learning test also evaluates hands-on programming skills of the applicant.The assessment features work-sample tasks such as:Tuning hyperparameters to optimize model performance.Diagnosing and mitigating issues of overfitting and underfitting.Building models using Python libraries such as NumPy, pandas, and scikit-learn.A good machine learning practitioner needs to effectively balance model complexity with generalization, and make meaningful conclusions based on predictions from models.

Instructions

Assessment Instructions General InstructionsThis test consists of 80 multiple-choice/theory questions.You may attempt the questions in any order.Use Python 3.8 or higher.Partial credit will be awarded for solutions that pass some (but not all) test cases.RulesDo not use external code from the internet.You may use Python’s standard library.All coding answers must run without syntax errors.For coding problems, efficiency will be considered—avoid unnecessary loops and high-complexity solutions.Follow Pythonic naming conventions and best practices.SubmissionIf this is an online platform test, click Submit after you’re satisfied.

Skills Evaluated