All You Need to know about BERT

This article was published as a part of the Data Science Blogathon Introduction Machines understand language through language representations. These language representations are in the form of vectors of real numbers. Proper language representation is necessary for a better understanding of the language by the machine. Language representations are of two types: (i) Context-free language representation such as Glove and Word2vec where embeddings for each token in the vocabulary are constant and it doesn’t depend on the context of the word. […]

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Analyzing customer feedbacks using Aspect Based Sentiment Analysis

This article was published as a part of the Data Science Blogathon Introduction With the advancement in technology, the growth of social media like Facebook, Twitter, Instagram has been a platform for the customers to give feedback to the businesses based on their satisfaction. The reviews posted by customers are the globally trusted source of genuine content for other users. Customer feedback serves as the third-party validation tool to build user trust in the brand. For understanding these customer feedbacks […]

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Part- 1: Step by Step Guide to Master Natural Language Processing (NLP) in Python

This article was published as a part of the Data Science Blogathon Introduction Computers and Machines are great while working with tabular data or Spreadsheets. However, human beings generally communicate in words and sentences, not in the form of tables or spreadsheets, and most of the information that humans speak or write is present in an unstructured manner. So it is not very understandable for computers to interpret these languages. Therefore, In natural language processing (NLP), our aim is to make […]

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NLP – Sentiment Analysis

Now, we can see that our target has changed to 0 and 1,i.e. 0 for Negative and 1 for Positive, and the data is more or less in a balanced state. Data Pre-processing Now, we will perform some pre-processing on the data before converting it into vectors and passing it to the machine learning model. We will create a function for pre-processing of data. 1. First, we will iterate through each record, and using a regular expression, we will get […]

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Rule-Based Sentiment Analysis in Python

This article was published as a part of the Data Science Blogathon     Image by Author made online on befunky.com Intro: According to experts, 80% of the world’s existing data is in the form of unstructured data(images, videos, text, etc). This data could be generated by Social media tweets/posts, call transcripts, survey or interview reviews, text across blogs, forums, news, etc. It is humanly impossible to read all the text across the web and find patterns. Yet, there is definitely […]

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Can Python understand human feelings through words? – A brief intro to NLP and VADER Sentiment Analysis

This article was published as a part of the Data Science Blogathon Introduction Imagine having the power to observe your customer’s thoughts, like what they really think of a particular product/service. For instance, there is a new product launched by NIKE and REEBOK. Both the companies launched a pair of new sports shoes and posted them on their social media accounts like Instagram or Facebook for marketing purposes. Is it possible for an individual to check all the thousands or lakhs […]

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Part- 3: Step by Step Guide to Master Natural Language Processing (NLP) in Python

This article was published as a part of the Data Science Blogathon Introduction This article is part of an ongoing blog series on Natural Language Processing (NLP). In part-1and  part-2 of this blog series, we complete the theoretical concepts related to NLP. Now, in continuation of that part, in this article, we will cover some of the new concepts. In this article, we will understand the terminologies required and then we start our journey towards text cleaning and preprocessing, which is […]

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Must Known Techniques for text preprocessing in NLP

This article was published as a part of the Data Science Blogathon In any Machine learning task, cleaning or preprocessing the data is as important as model building. Text data is one of the most unstructured forms of available data and when comes to deal with Human language then it’s too complex. Have you ever wondered how Alexa, Siri, Google assistant can understand, process, and respond in Human language. NLP is a technology that works behind it where before any response […]

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Language Translation with Transformer In Python!

This article was published as a part of the Data Science Blogathon Introduction Natural Language Processing (NLP) is a field at the convergence of artificial intelligence, and linguistics. The aim is to make the computers understand real-world language or natural language so that they can perform tasks like Question Answering, Language Translation, and many more. NLP has lots of applications in different fields. 1. NLP enables the recognition and prediction of diseases based on electronic health records. 2. It is used […]

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Develop a Customer Review Analysis Platform from scratch

This article was published as a part of the Data Science Blogathon Introduction When we go to buy anything, what is the one factor that helps us choosing one thing over another? Isn’t it the reviews of that product or service, which represent the brand value? In the era of digital advancement and e-commence, almost every product or service has an indirect or direct digital presence. Consumers of these products and services leave feedback on these over various mediums which creates […]

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