Natural Language Processing (NLP) Online Test

Candidates Assessed

28626+

Organisations Served

125+

iMocha’s Natural Language Processing (NLP) online test is the preferred pre-employment test for recruiters and hiring managers to hire job-fit candidates for roles such as Software Engineer – NLP, Natural Language Processing - Technical Architect, and Natural Language Processing Engineer. Our test helps to reduce hiring time by 45%.

About Natural Language Processing (NLP) Online Test

The Natural Language Processing (NLP) assessment test has been designed and developed by Subject Matter Experts (SME) to evaluate NLP skills of natural language processing Specialists- as per industry standards.

Natural Language Processing (NLP) is a computer science field along with artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora.

Natural Language Processing (NLP) online test helps hiring managers & employers to validate the NLP analysis skills of an applicant before an interview. Weed out irrelevant candidates using Natural Language Processing (NLP) pre-employment test and spend time interviewing only the relevant candidates. Get the detailed reports of test results instantly.

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Test Summary

This Natural Language Processing (NLP) skill test may contain MCQ's (Multiple Choice Questions), MAQ's (Multiple Answer Questions), Fill in the Blanks, Descriptive, Whiteboard Questions, Audio / Video Questions, AI-LogicBox, Coding Simulations, True or False Questions, etc.

Online Natural Language Processing (NLP) test is designed considering EEOC guidelines, it will help you assess & hire diverse talent without any bias.

Test Duration: 20 minutes

No. of Questions: 10

Level of Expertise: Entry/Mid/Expert

Useful for hiring

  • Software Engineer – NLP
  • Natural Language Processing - Technical Architect
  • Natural Language Processing Engineer

Topics Covered


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Algorithms for Sentence Classification

iMocha’s Natural Language Processing (NLP) online test helps recruiters and hiring managers to evaluate candidate’s understanding about sentence classification algorithms which helps to categorize data into a category

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Dimensionality Reduction in NLP

Our assessment evaluates candidate’s knowledge about dimensionality reduction self-learning technique by using machine learning by reducing input variables in dataset

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Word2Vec

This Natural Language Processing (NLP) assessment test assesses applicant’s knowledge about word2vec technique which helps to detect and suggest synonymous words for a sentence

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Singular Value Decomposition

Our test assesses applicant’s knowledge about singular value decomposition which helps in text mining

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Information Retrieval

Our Natural Language Processing (NLP) skill test evaluates applicant’s understanding about information retrieval technique that is used to get some appropriate information from text data

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Activation Functions

This assessment evaluates validates applicant’s knowledge about activation functions in NLP which defines the output of node from a set of input

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Optimizers

Our Natural Language Processing (NLP) pre-employment test evaluates candidate’s understanding about optimizer algorithms which are used to improve efficiency of data learning rate

Sample Questions

Choose from our 100,000+ question library or add your own questions to make powerful custom tests

Question types:

Multiple Option

Topic:

Word2Vec

Difficulty:

Easy


Q 1. In word vector quantization, one of the problems is that the relative position of words concerning the target word matters a lot. Which of the following seems a good weight term to multiply with each word?
1/relative_position
 
Relative_position
 
(relative_position)^2
 
None of the mentioned
 

Question types:

Multiple Option

Topic:

LSTM

Difficulty:

Hard


Q 2. Which of the following formulae is used as "forget gate" in LSTM (Long Short Term Memory Network)?

Here xt denotes input in LSTM at time t and ht denotes computed hidden state in LSTM at time t.
ft = σ(Wf * [ht, xt] + bf)
 
ft = σ(Wf * [ht-1, xt] + bf)
 
ft = σ(Wf * [ht , xt-1] + bf)
 
ft = σ(Wf * [ht-1, xt-1] + bf)
 

Question types:

Multiple Answer

Topic:

Linguistic

Difficulty:

Hard


Q 3. Which of the following is the ambiguous meaning of the given sentence?
"He never drinks coffee."

Note: There can be multiple correct answers to this question.
Someone else drinks coffee.
 
He NEVER EVER drinks coffee.
 
He never DRINKS coffee. (he uses it in some other means)
 
He never drinks COFFEE. (he drinks something else)
 

Sample Report

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Skill wise performance report by iMocha

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Trusted By

Vipin Sharma, Mobile Programming
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“Thanks to Customer Success Team of iMocha, they have shared the best practices of quick test creation & also helped us in training all our recruiters for various functionalities of the tool. Now my team of 25 recruiters has adopted this measure & it has done wonders for our clients.”

Vipin Sharma, Mobile Programming

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