Clock
Test duration:
20
min
Notes
No. of questions:
10
Tie
Level of experience:

PyTorch Test

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About

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. 

 

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  

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.

 

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. 

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How it works

Test Summary

Test Duration
20
No. of Questions
10
Level of Expertise
Useful for hiring
  • Data Scientist
  • Deep Learning
  • Python Developer
  • Machine Learning Engineer
Topics Covered
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Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.

Question types :

Multiple Option

Topic:

Difficulty:

Hard


Q 1. You have been asked to train « Naive Bayes model for spam detection dataset

Using Python command, what wil you add in the given code at XXXX to deciore, it and train your modal for the given dataset?

import numpy os np

X= nporroyll 3. 2b[1 21 [2.21.[3,21)
Y= nporray(fi.a,a.1))

XXXX

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

Question types :

Multiple Option

Topic:

Machine teaming

Difficulty:

Hard


Q 1. Q2 Lets assume that you have 6 Pandas DataFrome(af) in the below tole.

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074

When the following commend is executed, what hoppens to the DatoFrome?

df= defiinat()
Y= nporray(fi.a,a.1))

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
it gives an error becouse of the third row which has on empty string.
None of these

Question types :

Multiple Option

Topic:

PyTorch

Difficulty:

Easy

Question:

You are training a binarized neural network in PyTorch. Clamping of neuron outputs is an extremely important step in training such networks. Which of the following functions lets you clamp a given tensor in the range [-1, 1]?
A) torch.clamp(a, min=-1, max=1)
B) torch.limit(a, min=-1, max=1)


Options

  • A
  • B
  • Both A and B
  • None of the options
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