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

Deep Learning Test

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About

Deep Learning Online Test

Deep Learning is the subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning is one aspect of artificial intelligence (AI) that is concerned with emulating humans’ learning approach to gain certain types of knowledge. In simple terms, deep learning can be thought of as a way to automate predictive analytics.

The deep learning online test helps to hire managers & recruiters to find the best suitable candidates by assessing their ability to work on deep neural network models. The deep learning assessment test questions are designed & validated by industry experts to assess & hire deep learning engineers per industry standards.

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How it works

Test Summary

The online deep learning test helps to screen the candidates who possess the following traits:

1. Excellent understanding of Machine Learning algorithms & principles

2. Ability to work on Deep NN models for image classification, object detection, and semantic segmentation

3. Strong experience in developing Deep Learning Neural Networks on mobile platforms

4. Ability to build data processing pipelines and Deep Learning algorithms for sequencing data


iMocha’s powerful reporting & intelligent analytics will help you overview candidates' performance in each section within a glance. The candidate feedback module will ensure candidates have an excellent experience with iMocha.

The deep learning assessment test contains the latest & high-quality set of scenario-based questions to assess the operational experience of the candidate. Moreover, you can add your own questions as per the job requirement.

The deep learning skills test will evaluate the candidate’s practical knowledge and will identify whether the candidate is ready to be employed.

The deep learning pre-employment test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Descriptive Questions, Whiteboard Questions, Audio / Video Questions, AI-LogicBox (AI-based Pseudo-Coding Platform), Coding Simulations, True or False Questions, etc.

Test Duration
20
No. of Questions
10
Level of Expertise
Useful for hiring
  • Deep Learning Engineer
  • Research Engineer - Deep Learning
  • Deep Learning Developer
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:

Neural Networks

Difficulty:

Easy

Question:

Your boss asked you to do sentiment analysis using convolutional neural networks.
Knowing that convolutional neural networks are well-known for good performance in images, how will you react?


Options

  • You can't use convolutional neural networks for natural language processing.
  • It's totally wrong. Recurrent neural networks are better to use for this.
  • It's totally alright. Convolutional neural networks can also be used for natural language processing.
  • It's totally okay. We just need to reconstruct the documents to images before applying convolutional neural networks.
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FAQ
What is Data Science?
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