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PyTorch Test

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HomeMachine Learning Tests
PyTorch Test
Test duration:
20
min
No. of questions:
10
Level of experience:
Entry/Mid/Senior

PyTorch Test

The PyTorch Test helps recruiters and hiring managers assess a candidate;s proficiency in building, training, and managing neural networks using PyTorch. It enables organizations to streamline hiring for machine learning engineers, data scientists, and AI developers by evaluating candidates' skills in tensor operations, model structuring, forward computation, and modular implementations.

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The PyTorch logo
Capgemini
Deloitte
The United Nations
Fujitsu
The United Nations

PyTorch Skills Test

PyTorch is developed by Facebook's AI Research lab and is known as an open-source machine learning library based on the Torch library. It is mostly used for applications like computer vision and Natural Language Processing. PyTorch library can be used with both languages- Python and C++.

PyTorch uses core Python concepts such as classes, structures, and conditional loops that are familiar and more intuitive to understand. It mainly uses the primary and familiar programming paradigms rather than inventing its own.

PyTorch skills test helps tech recruiters and hiring managers assess candidates' PyTorch skills. The PyTorch online test is designed by experienced subject matter experts (SMEs) to evaluate and hire PyTorch experts as per industry standards.

The PyTorch 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.

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How it works

Test Summary

PyTorch skills test helps to screen the candidates who possess traits as follows:

  • Good knowledge of various computations in the PyTorch library
  • Experience with PyTorch model methods and PyTorch tensor
  • Understanding of new network models, GPU devices, and optimizers
  • Familiarity with terms like functions, objects, and classes

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

Useful for hiring
  • Data Scientist
  • Deep Learning
  • Python Developer
  • Machine Learning Engineer
Test Duration
20
min
No. of Questions
10
Level of Expertise
Entry/Mid/Senior
Topics Covered
Shuffle

PyTorch Tensor

This test assesses candidates' ability to manipulate tensors for data storage, transformation, and computation within neural networks.

Modular Implementation

This test evaluates how candidates organize and reuse model components using PyTorch’s module-based architecture.
Shuffle

Computation in PyTorch

This test assesses candidates' understanding of computation graphs, forward and backward passes, and automatic differentiation in PyTorch.
Shuffle

Network Models

This test evaluates candidates' ability to define, initialize, and train neural network models using nn.Module and its subclasses.
Shuffle

Functions

This test assesses how candidates use built-in and custom functions to perform mathematical operations and network logic in PyTorch.
Shuffle

Objects

This test evaluates candidates' use of object-oriented design in PyTorch to structure and manage model components, layers, and utilities.
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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.
Book a demo
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