iMocha's Machine Learning coding test enables recruiters and hiring managers to assess Python programming skills for Machine Learning. Machine test for python can be useful in hiring Data Scientists, Data Science engineers, Data Science developers, Data Science associates, Data Analysts, and Machine Learning engineers. Our test can help you reduce hiring cost by 40%.
Machine learning with Python is a type of data science technique in which programmers work with machine learning algorithms to put data into effective work. Machine Learning with Python mainly focuses on the development of various computer programs that can help the programmer to change it when exposed to new data.
The machine learning coding test helps recruiters & hiring managers to assess candidates’ Python programming skills for machine learning. Machine test for Python is designed by experienced Subject Matter Experts (SME) to evaluate and hire machine learning engineer as per the industry standards.
Test Duration: 60 minutes
No. of Questions: 22
Level of Expertise: Entry/Mid/Expert
The machine learning coding test evaluates the candidate's understanding and the use of Classification and Regression Algorithms
Machine test for Python evaluates candidate's knowledge of Bootstrapping to avoid overfitting and improves the stability of the machine learning algorithm
The test contains questions on types of Machine learning to measure candidate's in-depth understanding of ML
Machine Learning coding test assesses a candidate's knowledge of preparing data for analysis by removing or modifying data that is incorrect, incomplete, irrelevant, duplicated, or improperly formatted
The tech assessment evaluates candidates based on their knowledge of the Scikit-learn library which contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction
The Machine test for Python gauges a candidate's knowledge on interdisciplinary field of research related to Natural Language Processing, Programming Language Structure, and Social and History analysis such contributions graphs and commit time series
Choose from our 100,000+ question library or add your own questions to make powerful custom tests
Classification and Regression Algorithms - Bayesian Parameter Selection
Model Selection and Performance - Basic Concepts
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