Text processing example with NLTK and spaCy. In this article, I am going to demonstrate text processing in Python.
The Internet has connected the world, while Social Media like Facebook, Twitter and Reddit provided the platform for people to express their opinions and feelings toward a topic. Then, the proliferation of smartphones increased the usage of these platforms directly. For instance, there are 96% or 2,240 million Facebook active users who used Facebook by smartphones and tablets [1]. The increment in the usage of Social Media has grown the size of text data, and boost the studies or researches in Natural Language Processing (NLP), for example, Information Retrieval and Sentiment Analysis. Most of the time, the documents or the text files to be analyzed are gigantic and contains a lot of noise, directly used raw texts for analysis is inapplicable. Hence, text processing is essential to provide clean input for modelling and analysis
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In Conversation With Dr Suman Sanyal, NIIT University,he shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
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There is an incredible number of data mining tools available in the market. This article seeks to explain the best options for each function and context.