Why you should use PyTorch Test?

The ПИТОРЧ ТЕСТ makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects: Создание и манипулирование тензорами Pytorch Использование наборов данных и DataLoaders в Pytorch Применение преобразования в Pytorch Строительные модели с Pytorch Оптимизация параметров модели с Pytorch Понимание основных основах Основы питона и синтаксис Программирование в Python Работа с Python Packages и библиотеками Манипуляция и анализ данных в Python

PyTorch Test

Q: What topics are covered in the PyTorch Test?

Тенсоры Pytorch Наборы данных и DataLoaders в Pytorch Преобразования в Pytorch Строительные модели с Pytorch Оптимизирование параметров модели с pytorch Основы науки данных Основы питона Программирование в Python

About the test:

Тест Pytorch оценивает знания и навыки кандидата в Pytorch, популярной структуре глубокого обучения. Он оценивает их понимание науки о данных, глубокого обучения, машинного обучения, Python, Python Pandas, Python Linux, Numpy и структур данных.

Covered skills:

Тенсоры Pytorch
Преобразования в Pytorch
Оптимизирование параметров модели с pytorch
Основы питона

Наборы данных и DataLoaders в Pytorch
Строительные модели с Pytorch
Основы науки данных
Программирование в Python

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9 reasons why

Adaface PyTorch Assessment Test is the most accurate way to shortlist Ученый данныхs

Reason #1

Tests for on-the-job skills

The PyTorch Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

Понимание и работа с тензорами Pytorch
Создание и использование наборов данных и данных DataLoAders в Pytorch
Применение преобразования в Pytorch
Строительные модели с Pytorch
Оптимизация параметров модели с Pytorch
Реализация основополагающих наук о данных
Демонстрирование мастерства в основах Python
Эффективное программирование в Python

Reason #2

No trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

View sample questions

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface

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Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

Это лишь небольшая выборка из нашей библиотеки из более чем более 10000 вопросов. Фактические вопросы по этому поводу ПИТОРЧ ТЕСТ будет не подлежащим гугливым.

🧐 Question
Medium ZeroDivisionError and IndexError Exceptions	Try practice test
What will the following Python code output?
Medium Session File Handling Dictionary	Try practice test
The function high_sess should compute the highest number of events per session of each user in the database by reading a comma-separated value input file of session data. The result should be returned from the function as a dictionary. The first column of each line in the input file is expected to contain the user’s name represented as a string. The second column is expected to contain an integer representing the events in a session. Here is an example input file: Tony,10 Stark,12 Black,25 Your program should ignore a non-conforming line like this one. Stark,3 Widow,6 Widow,14 The resulting return value for this file should be the following dictionary: { 'Stark':12, 'Black':25, 'Tony':10, 'Widow':14 } What should replace the CODE TO FILL line to complete the function?
Medium Max Code Arrays	Try practice test
Below are code lines to create a Python function. Ignoring indentation, what lines should be used and in what order for the following function to be complete:
Medium Recursive Function Recursion Dictionary Lists	Try practice test
Consider the following Python code: In the above code, recursive_search is a function that takes a dictionary (data) and a target key (target) as arguments. It searches for the target key within the dictionary, which could potentially have nested dictionaries and lists as values, and returns the value associated with the target key. If the target key is not found, it returns None. nested_dict is a dictionary that contains multiple levels of nested dictionaries and lists. The recursive_search function is then called with nested_dict as the data and 'target_key' as the target. What will the output be after executing the above code?
Medium Stacking problem Stack Linkedlist	Try practice test
What does the below function ‘fun’ does? A: Sum of digits of the number passed to fun. B: Number of digits of the number passed to fun. C: 0 if the number passed to fun is divisible by 10. 1 otherwise. D: Sum of all digits number passed to fun except for the last digit.
Medium Amazon electronics product feedback	Try practice test
Amazon's electronics store division has over the last few months focused on getting customer feedback on their products, and marking them as safe/ unsafe. Their data science team has used decision trees for this. The training set has these features: product ID, data, summary of feedback, detailed feedback and a binary safe/unsafe tag. During training, the data science team dropped any feedback records with missing features. The test set has a few records with missing "detailed feedback" field. What would you recommend? A: Remove the test samples with missing detailed feedback text fields B: Generate synthetic data to fill in missing fields C: Use an algorithm that handles missing data better than decision trees D: Fill in the missing detailed feedback text field with the summary of feedback field.
Easy Fraud detection model Logistic Regression	Try practice test
Your friend T-Rex is working on a logistic regression model for a bank, for a fraud detection usecase. The accuracy of the model is 98%. T-Rex's manager's concern is that 85% of fraud cases are not being recognized by the model. Which of the following will surely help the model recognize more than 15% of fraud cases?
Medium Rox's decision tree classifier Decision Tree Classifier	Try practice test
Your data science intern Rox was asked to create a decision tree classifier with 12 input variables. The tree used 7 of the 12 variables, and was 5 levels deep. Few nodes of the tree contain 3 data points. The area under the curve (AUC) is 0.86. As Rox's mentor, what is your interpretation? A. The AUC is high, and the small nodes are all very pure- the model looks accurate. B. The tree might be overfitting- try fitting shallower trees and using an ensemble method. C. The AUC is high, so overall the model is accurate. It might not be well-calibrated, because the small nodes will give poor estimates of probability. D. The tree did not split on all the input variables. We need a larger data set to get a more accurate model.

	🧐 Question	🔧 Skill
	Medium ZeroDivisionError and IndexError Exceptions	2 mins Python	Try practice test
What will the following Python code output?
	Medium Session File Handling Dictionary	2 mins Python	Try practice test
The function high_sess should compute the highest number of events per session of each user in the database by reading a comma-separated value input file of session data. The result should be returned from the function as a dictionary. The first column of each line in the input file is expected to contain the user’s name represented as a string. The second column is expected to contain an integer representing the events in a session. Here is an example input file: Tony,10 Stark,12 Black,25 Your program should ignore a non-conforming line like this one. Stark,3 Widow,6 Widow,14 The resulting return value for this file should be the following dictionary: { 'Stark':12, 'Black':25, 'Tony':10, 'Widow':14 } What should replace the CODE TO FILL line to complete the function?
	Medium Max Code Arrays	2 mins Python	Try practice test
Below are code lines to create a Python function. Ignoring indentation, what lines should be used and in what order for the following function to be complete:
	Medium Recursive Function Recursion Dictionary Lists	3 mins Python	Try practice test
Consider the following Python code: In the above code, recursive_search is a function that takes a dictionary (data) and a target key (target) as arguments. It searches for the target key within the dictionary, which could potentially have nested dictionaries and lists as values, and returns the value associated with the target key. If the target key is not found, it returns None. nested_dict is a dictionary that contains multiple levels of nested dictionaries and lists. The recursive_search function is then called with nested_dict as the data and 'target_key' as the target. What will the output be after executing the above code?
	Medium Stacking problem Stack Linkedlist	4 mins Python	Try practice test
What does the below function ‘fun’ does? A: Sum of digits of the number passed to fun. B: Number of digits of the number passed to fun. C: 0 if the number passed to fun is divisible by 10. 1 otherwise. D: Sum of all digits number passed to fun except for the last digit.
	Medium Amazon electronics product feedback	2 mins Data Science	Try practice test
Amazon's electronics store division has over the last few months focused on getting customer feedback on their products, and marking them as safe/ unsafe. Their data science team has used decision trees for this. The training set has these features: product ID, data, summary of feedback, detailed feedback and a binary safe/unsafe tag. During training, the data science team dropped any feedback records with missing features. The test set has a few records with missing "detailed feedback" field. What would you recommend? A: Remove the test samples with missing detailed feedback text fields B: Generate synthetic data to fill in missing fields C: Use an algorithm that handles missing data better than decision trees D: Fill in the missing detailed feedback text field with the summary of feedback field.
	Easy Fraud detection model Logistic Regression	2 mins Data Science	Try practice test
Your friend T-Rex is working on a logistic regression model for a bank, for a fraud detection usecase. The accuracy of the model is 98%. T-Rex's manager's concern is that 85% of fraud cases are not being recognized by the model. Which of the following will surely help the model recognize more than 15% of fraud cases?
	Medium Rox's decision tree classifier Decision Tree Classifier	2 mins Data Science	Try practice test
Your data science intern Rox was asked to create a decision tree classifier with 12 input variables. The tree used 7 of the 12 variables, and was 5 levels deep. Few nodes of the tree contain 3 data points. The area under the curve (AUC) is 0.86. As Rox's mentor, what is your interpretation? A. The AUC is high, and the small nodes are all very pure- the model looks accurate. B. The tree might be overfitting- try fitting shallower trees and using an ensemble method. C. The AUC is high, so overall the model is accurate. It might not be well-calibrated, because the small nodes will give poor estimates of probability. D. The tree did not split on all the input variables. We need a larger data set to get a more accurate model.

	🧐 Question	🔧 Skill	💪 Difficulty	⌛ Time
	ZeroDivisionError and IndexError Exceptions	Python	Medium	2 mins	Try practice test
What will the following Python code output?
	Session File Handling Dictionary	Python	Medium	2 mins	Try practice test
The function high_sess should compute the highest number of events per session of each user in the database by reading a comma-separated value input file of session data. The result should be returned from the function as a dictionary. The first column of each line in the input file is expected to contain the user’s name represented as a string. The second column is expected to contain an integer representing the events in a session. Here is an example input file: Tony,10 Stark,12 Black,25 Your program should ignore a non-conforming line like this one. Stark,3 Widow,6 Widow,14 The resulting return value for this file should be the following dictionary: { 'Stark':12, 'Black':25, 'Tony':10, 'Widow':14 } What should replace the CODE TO FILL line to complete the function?
	Max Code Arrays	Python	Medium	2 mins	Try practice test
Below are code lines to create a Python function. Ignoring indentation, what lines should be used and in what order for the following function to be complete:
	Recursive Function Recursion Dictionary Lists	Python	Medium	3 mins	Try practice test
Consider the following Python code: In the above code, recursive_search is a function that takes a dictionary (data) and a target key (target) as arguments. It searches for the target key within the dictionary, which could potentially have nested dictionaries and lists as values, and returns the value associated with the target key. If the target key is not found, it returns None. nested_dict is a dictionary that contains multiple levels of nested dictionaries and lists. The recursive_search function is then called with nested_dict as the data and 'target_key' as the target. What will the output be after executing the above code?
	Stacking problem Stack Linkedlist	Python	Medium	4 mins	Try practice test
What does the below function ‘fun’ does? A: Sum of digits of the number passed to fun. B: Number of digits of the number passed to fun. C: 0 if the number passed to fun is divisible by 10. 1 otherwise. D: Sum of all digits number passed to fun except for the last digit.
	Amazon electronics product feedback	Data Science	Medium	2 mins	Try practice test
Amazon's electronics store division has over the last few months focused on getting customer feedback on their products, and marking them as safe/ unsafe. Their data science team has used decision trees for this. The training set has these features: product ID, data, summary of feedback, detailed feedback and a binary safe/unsafe tag. During training, the data science team dropped any feedback records with missing features. The test set has a few records with missing "detailed feedback" field. What would you recommend? A: Remove the test samples with missing detailed feedback text fields B: Generate synthetic data to fill in missing fields C: Use an algorithm that handles missing data better than decision trees D: Fill in the missing detailed feedback text field with the summary of feedback field.
	Fraud detection model Logistic Regression	Data Science	Easy	2 mins	Try practice test
Your friend T-Rex is working on a logistic regression model for a bank, for a fraud detection usecase. The accuracy of the model is 98%. T-Rex's manager's concern is that 85% of fraud cases are not being recognized by the model. Which of the following will surely help the model recognize more than 15% of fraud cases?
	Rox's decision tree classifier Decision Tree Classifier	Data Science	Medium	2 mins	Try practice test
Your data science intern Rox was asked to create a decision tree classifier with 12 input variables. The tree used 7 of the 12 variables, and was 5 levels deep. Few nodes of the tree contain 3 data points. The area under the curve (AUC) is 0.86. As Rox's mentor, what is your interpretation? A. The AUC is high, and the small nodes are all very pure- the model looks accurate. B. The tree might be overfitting- try fitting shallower trees and using an ensemble method. C. The AUC is high, so overall the model is accurate. It might not be well-calibrated, because the small nodes will give poor estimates of probability. D. The tree did not split on all the input variables. We need a larger data set to get a more accurate model.

Reason #4

1200+ customers in 75 countries

С помощью Adaface мы смогли оптимизировать первоначальный процесс отбора более чем на 75 %, высвободив драгоценное время как для менеджеров по найму, так и для нашей команды по привлечению талантов!

Brandon Lee, Глава отдела кадров, Love, Bonito

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Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment ПИТОРЧ ТЕСТ in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Science behind Adaface tests

Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the ПИТОРЧ ТЕСТ from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

Reason #7

Detailed scorecards & benchmarks

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Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

Reason #9

Advanced Proctoring

Learn more

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About the PyTorch Online Test

Why you should use Pre-employment PyTorch Test?

The ПИТОРЧ ТЕСТ makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

Создание и манипулирование тензорами Pytorch
Использование наборов данных и DataLoaders в Pytorch
Применение преобразования в Pytorch
Строительные модели с Pytorch
Оптимизация параметров модели с Pytorch
Понимание основных основах
Основы питона и синтаксис
Программирование в Python
Работа с Python Packages и библиотеками
Манипуляция и анализ данных в Python

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the PyTorch Test?

тензоры Pytorch
Тенсоры Pytorch представляют собой мощные многомерные массивы, используемые для эффективного вычисления и хранения численных данных. Они предоставляют гибкий и удобный способ представления и манипулирования данными в Pytorch, что делает его важным навыком для измерения в этом тесте. Разрешить эффективную обработку и обработку крупномасштабных наборов данных. Эти компоненты обеспечивают легкую загрузку, преобразование и пакетирование, которые имеют решающее значение для обучения и оценки моделей машинного обучения. и дополнить данные. Они включают такие задачи, как изменение размера, обрезка и нормализация данных, повышение качества и разнообразия ввода для моделей. Экспертиза тестирования в преобразовании Pytorch важна для обеспечения надежной и эффективной подготовки данных. архитектуры. Этот навык имеет решающее значение для разработки моделей, адаптированных к конкретным задачам, обеспечивая гибкость и инновации в приложениях машинного обучения. и градиент спуск для эффективного обновления и оптимизации весов модели. Этот навык имеет важное значение для повышения производительности модели и достижения более высокой точности в задачах машинного обучения. данные. Измерение этого навыка гарантирует, что кандидат обладает основополагающими знаниями, необходимыми для эффективной работы с данными и принятия обоснованных решений. Измерение этого навыка гарантирует, что кандидат обладает необходимыми знаниями для написания и понимания кода Python, который широко используется в анализе данных и машинном обучении. Применение языковых навыков питона для решения реальных проблем. Этот навык измеряет мастерство кандидата в реализации алгоритмов, написании эффективного кода и справедливости с различными структурами данных, которые важны в контексте разработки и развертывания моделей машинного обучения.
Full list of covered topics
The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for ПИТОРЧ ТЕСТ to be based on.
Тенсоры Pytorch
Pytorch Autograd
Pytorch вперед и обратное распространение
Обучение модели Pytorch
Функции потери питтера
Функции активации Pytorch
Оптимизаторы Pytorch
Нагрузка данных Pytorch
Увеличение данных Pytorch
Предварительная обработка данных Pytorch
Расщепление наборов данных Pytorch
Архитектура модели Pytorch
Оценка модели Pytorch
Настройка гиперпараметра Pytorch
Принципы науки о данных
статистический анализ
Визуализация данных
Алгоритмы машинного обучения
Синтаксис Python и типы данных
Условные заявления
Петли и итерации
Функции и модули
Обработка файлов
Объектно-ориентированного программирования
Обработка исключений
Структуры данных
Базовые взаимодействия SQL и базы данных
Обычные выражения
Методы отладки
Оптимизация кода
Документация и комментирование
Модульное тестирование на Python

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What roles can I use the PyTorch Test for?

Ученый данных
Инженер машинного обучения
Инженер глубокого обучения
Аналитик данных
Разработчик Python
Инженер-программист
Научный сотрудник
Инженер искусственного интеллекта
Инженер данных
Данные архитектор

How is the PyTorch Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

Реализация алгоритмов машинного обучения с помощью pytorch
Оценка моделей машинного обучения с использованием pytorch
Понимание нейронных сетей и глубокого обучения
Применение методов для обучения нейронной сети
Внедрение сверточных нейронных сетей (CNNS)
Работа с повторяющимися нейронными сетями (RNNS)
Использование переноса обучения в Pytorch
Внедрение обработки естественного языка (NLP) с помощью Pytorch
Применение методов компьютерного зрения с помощью pytorch
Внедрение алгоритмов обучения подкреплению с помощью Pytorch

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Менеджеры по найму чувствовали, что с помощью технических вопросов, которые они задавали во время групповых собеседований, они могли определить, какие кандидаты имеют более высокие баллы, и отличиться от тех, кто не набрал таких же баллов. Они есть очень доволен с качеством кандидатов, включенных в шорт-лист отбора Adaface.

85%

Сокращение времени проверки

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PyTorch Hiring Test Часто задаваемые вопросы

Могу ли я объединить несколько навыков в одну пользовательскую оценку?

Да, конечно. Пользовательские оценки настроены на основе вашей должности и будут включать вопросы по всем необходимым навыкам, которые вы указываете.

Есть ли у вас какие-либо функции против Chating или Proctoring?

У нас есть следующие функции антихиализации:

Необъемлющие вопросы
IP Proctoring
Веб -прокторинг
Веб -камера Proctoring
Обнаружение плагиата
Безопасный браузер

Узнайте больше о функциях Proctoring.

Как мне интерпретировать результаты тестов?

Основная вещь, которую нужно помнить, это то, что оценка - это инструмент устранения, а не инструмент отбора. Оценка навыков оптимизирована, чтобы помочь вам устранить кандидатов, которые технически не имеют квалификации для этой роли, она не оптимизирована, чтобы помочь вам найти лучшего кандидата на роль. Таким образом, идеальный способ использования оценки - определить пороговый балл (обычно 55%, мы помогаем вам сравнить) и пригласить всех кандидатов, которые забивают выше порога для следующих раундов интервью.

На каком уровне опыта я могу использовать этот тест?

Каждая оценка Adaface настроена на ваш инструкции/ Идеальный кандидат (наши эксперты по предметам выберут правильные вопросы для вашей оценки из нашей библиотеки из 10000+ вопросов). Эта оценка может быть настроена для любого уровня опыта.

Каждый кандидат получает одинаковые вопросы?

Да, вам намного проще сравнить кандидатов. Варианты для вопросов MCQ и порядок вопросов рандомизированы. У нас есть против Chating/Proctoring. В нашем плане предприятия у нас также есть возможность создать несколько версий одной и той же оценки с вопросами аналогичных уровней сложности.