Scikit-learn Test

Test duration:

min

No. of questions:

Level of experience:

Expert

Scikit-learn Test

This Scikit-learn Test evaluates candidates' proficiency in building machine learning models, applying algorithms, and data preprocessing using Scikit-learn. Recruiters can assess problem-solving and analytical capabilities for data science roles. With iMocha’s skill-based assessments, organizations can confidently hire data professionals who deliver accurate predictions and actionable insights through machine learning applications.

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Scikit-learn Online Test

Scikit-learn is a free software machine learning library mainly used for the Python programming language. It also helps to provide a range of supervised and unsupervised learning algorithms via a consistent interface in Python. Scikit-learn library is licensed under a permissive simplified BSD license and is distributed under many Linux distributions, encouraging academic and commercial use.

Scikit-learn online test helps tech recruiters and hiring managers to assess candidates' machine learning skills with Scikit-learn. Scikit-learn skills test is designed by experienced subject matter experts (SMEs) to evaluate and hire machine learning engineers as per industry standards.

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How it works

Test Summary

Scikit-learn online test helps to screen the candidates who possess traits as follows:

Good knowledge of Preprocessing, Classification, and Clustering in Scikit-learn
Experience in data cleaning and data manipulation processes
Understanding of Model Selection, Decision Tree, and Hyper-Parameter Tuning
Familiarity with terms like pipelining, encoding, and imputations

Scikit-learn skills test is a secure and reliable way of candidate assessment. You can use our role-based access control feature to restrict system access based on the roles of individual users within the recruiting team. Features like window violation, image, audio, and video proctoring help detect cheating during the test.

This test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Whiteboard Questions, Audio / Video Questions, LogicBox (AI-based Pseudo-Coding Platform), Coding Simulators, True or False Questions, etc.

Useful for hiring

Machine Learning Engineer
Data Scientist
Python Developer

Test Duration

min

No. of Questions

Level of Expertise

Expert

Topics Covered

Preprocessing

Assesses knowledge of data preprocessing techniques in Scikit-learn. Covers scaling, normalization, handling missing values, and transforming features using classes like StandardScaler, MinMaxScaler, and SimpleImputer.

Classification

Evaluates understanding of building classification models using Scikit-learn. Includes algorithms like logistic regression, decision trees, SVMs, and evaluating performance using accuracy, precision, recall, and ROC curves.

Clustering

Tests ability to perform unsupervised clustering with Scikit-learn. Focuses on algorithms such as K-Means, DBSCAN, and Agglomerative Clustering, including metrics like silhouette score.

Dimensionality Reduction

Assesses ability to reduce data dimensionality using techniques like PCA (Principal Component Analysis), TruncatedSVD, and t-SNE in Scikit-learn. Focuses on improving computational efficiency and visualizing high-dimensional data.

Pipelining

Evaluates understanding of creating and using Scikit-learn pipelines to streamline workflows. Includes chaining preprocessing steps and estimators, grid search within pipelines, and maintaining reproducibility.

Encoding

Tests familiarity with encoding categorical variables using Scikit-learn tools like OneHotEncoder, OrdinalEncoder, and custom transformers. Covers integration with pipelines and handling of unknown values.

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.

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FAQ

Test summary

Skills Assessed

Use data science test to hire

Data scientist assessment helps you to screen the traits below:

You can customize this test by

Setting the difficulty level of the test

Combining multiple skills into one

Adding your own questions

Requesting a tailor-made test

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Frequently Asked Questions

Scikit-learn Test