Top NLP interview questions with detail answers asked in top companies that will help you to crack the Natural Language Processing job interviews in 2020.
Natural Language Processing is a field of computer science that deals with communication between computer systems and humans. It is a technique used in Artificial Intelligence and Machine Learning. It is used to create automated software that helps understand human spoken languages to extract useful information from the data it gets in the form of audio. Techniques in NLP allow computer systems to process and interpret data in the form of natural languages.
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Stop words are said to be useless data for a search engine. Words such as articles, prepositions, etc. are considered as stop words. There are stop words such as was, were, is, am, the, a, an, how, why, and many more. In Natural Language Processing, we eliminate the stop words to understand and analyze the meaning of a sentence. The removal of stop words is one of the most important tasks for search engines. Engineers design the algorithms of search engines in such a way that they ignore the use of stop words. This helps show the relevant search result for a query.
Two real-life applications of Natural Language Processing are as follows:
TFIDF or Term Frequency-Inverse Document Frequency indicates the importance of a word in a set. It helps in information retrieval with numerical statistics. For a specific document, TF-IDF shows a frequency that helps identify the keywords in a document. The major use of TF-IDF in NLP is the extraction of useful information from crucial documents by statistical data. It is ideally used to classify and summarize the text in documents and filter out stop words.
TF helps calculate the ratio of the frequency of a term in a document and the total number of terms. Whereas, IDF denotes the importance of the term in a document.
The formula for calculating TF-IDF:
TF(W) = (Frequency of W in a document)/(The total number of terms in the document)
IDF(W) = log_e(The total number of documents/The number of documents having the term W)
When TF*IDF is high, the frequency of the term is less and vice versa.
Google uses TF-IDF to decide the index of search results according to the relevancy of pages. The design of the TF-IDF algorithm helps optimize the search results in Google. It helps quality content rank up in search results.
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Syntactic analysis is a technique of analyzing sentences to extract meaning from it. Using syntactic analysis, a machine can analyze and understand the order of words arranged in a sentence. NLP employs grammar rules of a language that helps in the syntactic analysis of the combination and order of words in documents.
The techniques used for syntactic analysis are as follows:
Semantic analysis helps make a machine understand the meaning of a text. It uses various algorithms for the interpretation of words in sentences. It also helps understand the structure of a sentence.
Techniques used for semantic analysis are as given below:
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NLTK is a Python library, which stands for Natural Language Toolkit. We use NLTK to process data in human spoken languages. NLTK allows us to apply techniques such as parsing, tokenization, lemmatization, stemming, and more to understand natural languages. It helps in categorizing text, parsing linguistic structure, analyzing documents, etc.
A few of the libraries of the NLTK package that we often use in NLP are:
Tokenization is a process used in NLP to split a sentence into tokens. Sentence tokenization refers to splitting a text or paragraph into sentences.
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In this tutorial, we’ll walk you through some of the most commonly asked C interview questions. Typically, a job interview commences by testing your basic knowledge of the subject (in this case, C programming language) and gradually moves on to exploring your practical skills in the domain.
In this ptutotial, we’ve created a list of 21 C++ interview questions that you should know if you aspire to build a career in Software Development. These C++ interview questions and answers will help you break the ice on the subject!
C is a powerful general-purpose programming language that supports procedural, imperative, and structured paradigms. It is used for developing operating systems, databases, and application software for a wide range of computer architectures (PLCs, embedded systems, etc.). C is an excellent beginner-friendly language with an easy learning curve.