PyTorch test
Summary of the PyTorch test
This test evaluates candidates’ knowledge of PyTorch and their ability to solve situational tasks using it. The test will help identify developers who are proficient in PyTorch and capable of implementing various deep learning models using the framework.
Covered skills
PyTorch fundamentals
Feed-forward network architecture in PyTorch
Convolutional neural network architectures in PyTorch
Complex neural architecture in PyTorch
Use the PyTorch test to hire
Deep learning engineers, machine-learning engineers,artificial intelligence engineers, data analysts, and any other roles requiring intermediate knowledge of PyTorch.
About the PyTorch test
PyTorch is an open-source machine learning library for Python that is widely used for developing and training deep learning models.
It is developed and maintained by Facebook's AI research lab and is designed to be easy to use and flexible, with a focus on providing strong support for training and inference on graphical processing units (GPUs). Pytorch makes it easy to implement complex models, such as those with branching or with loops. It also makes it easier to debug and optimize PyTorch code.
PyTorch also includes a number of high-level libraries and tools for tasks such as natural language processing and computer vision, as well as a number of pre-trained models that can be fine-tuned for a variety of tasks.
Hiring someone who is experienced with PyTorch will help your business to build and train deep learning models more quickly and efficiently, reducing the time and resources required to develop machine learning-based solutions. An experienced PyTorch developer will know how to design and train deep learning models that achieve good performance and help to improve the accuracy and effectiveness of your machine learning systems.
PyTorch's dynamic computational graph allows for greater flexibility in model design and training, which can make it easier to adapt your machine learning systems to new tasks or changing requirements or to integrate them with other tools and platforms.
This test covers the fundamentals of PyTorch, feed-forward network architecture, and working with convolutional neural network architecture and complex neural architecture in PyTorch.
Candidates who perform well on this test have a fundamental knowledge of core PyTorch functionalities and can make the best use of each one when working with different types of models. This test will help you hire candidates with the PyTorch skills necessary to help your company train large or complex machine learning systems that are easy to deploy and maintain.
The test is made by a subject-matter expert
Gary R.
Gary has been working in the data science field for more than three years and is proficient in the fields of machine learning and data analysis. He has a Bachelor’s degree in Economics and a Master’s degree in Computer Science. The combination of those two fields helps Gary to achieve even greater results.
He is fond of computer science and loves to work on projects related to Artificial Intelligence which is, in his opinion, the future of our world.
Crafted with expert knowledge
TestGorilla’s tests are created by subject matter experts. We assess potential subject-matter experts based on their knowledge, ability, and reputation. Before being published, each test is peer-reviewed by another expert, then calibrated using hundreds of test takers with relevant experience in the subject.
Our feedback mechanisms and unique algorithms allow our subject-matter experts to constantly improve their tests.
What our customers are saying
TestGorilla helps me to assess engineers rapidly. Creating assessments for different positions is easy due to pre-existing templates. You can create an assessment in less than 2 minutes. The interface is intuitive and it’s easy to visualize results per assessment.
VP of engineering, mid-market (51-1000 FTE)
Any tool can have functions—bells and whistles. Not every tool comes armed with staff passionate about making the user experience positive.
The TestGorilla team only offers useful insights to user challenges, they engage in conversation.
For instance, I recently asked a question about a Python test I intended to implement. Instead of receiving “oh, that test would work perfectly for your solution,” or, “at this time we’re thinking about implementing a solution that may or may not…” I received a direct and straightforward answer with additional thoughts to help shape the solution.
I hope that TestGorilla realizes the value proposition in their work is not only the platform but the type of support that’s provided.
For a bit of context—I am a diversity recruiter trying to create a platform that removes bias from the hiring process and encourages the discovery of new and unseen talent.
Chief Talent Connector, small business (50 or fewer FTE)
Use TestGorilla to hire the best faster, easier and bias-free
Our screening tests identify the best candidates and make your hiring decisions faster, easier, and bias-free.
Watch what TestGorilla can do for you
Create high-quality assessments, fast
Building assessments is a breeze with TestGorilla. Get started with these simple steps.
View a sample report
The PyTorch test will be included in a PDF report along with the other tests from your assessment. You can easily download and share this report with colleagues and candidates.
FAQs
Related tests
Python (Coding): Entry-Level Algorithms
Ember.js
C# (Coding): Entry-Level Algorithms
PHP (Coding): Intermediate-Level Algorithms
React
Java (Coding): Entry-Level Algorithms
Android Development Using Kotlin
Coding: Data Structures - Binary Search Trees
Coding: Data Structures - Heaps