A friendly guide to NLP: Bag-of-Words with Python example

1. A Quick Example Let’s look at an easy example to understand the concepts previously explained. We could be interested in analyzing the reviews about Game of Thrones: Review 1: Game of Thrones is an amazing tv series! Review 2: Game of Thrones is the best tv series! Review 3: Game of Thrones is so great In the table, I show all the calculations to obtain the Bag-Of-Words approach: Each row corresponds to a different review, while the rows are […]

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Text Generation Using Bidirectional LSTM – A Walk-through in Tensorflow

This article was published as a part of the Data Science Blogathon Text Generation The Text Generation is a Natural Language Processing task that involves automatically generating meaningful texts. We can also utilize the Text Generation process for Autocomplete. Initially, we provide a prompt, which is a text that is used as the base to generate texts. The model will generate texts based on the prompt, the predicted text will be added to the base prompt and it is fed again […]

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Build an end-end Currency Convertor chatbot with Python and Dialogflow

This article was published as a part of the Data Science Blogathon Introduction Hello all, Hope you are fine. In this tutorial we will learn how to create chatbots using Dialogflow and python, as well we will learn the deployment of chatbots to telegram. In our previous articles, we have learned to create a simple rule-based chatbot using simple python and NLTK libraries. I would like to request you to have a look at the article creating a simple chatbot […]

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New Anaphora and Co-reference Resolution Technique for Biographies

This article was published as a part of the Data Science Blogathon Introduction Biographies of many famous personalities are very insightful and inspiring. Although, one may not want to read the whole document. In order to just get the important points from the biography, one can generate a summary of the biography. The summary is generated by giving weights to all the words. Sometimes, anaphoras can be predicted by the machine as a separate word which in return produces a less […]

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Sentiment Analysis Using Bidirectional Stacked LSTM

This article was published as a part of the Data Science Blogathon Sentiment Analysis Sentiment Analysis is the process of finding the sentiments of the text data. Sentiment Analysis falls under the text classification in Natural Language Processing. Sentiment Analysis would help us to know our customer reviews better. A sentiment denotes any one of the following, Positive, Negative, and Neutral. When we analyze the negative reviews of our products we can easily use those reviews to surmount the problems […]

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Email Spam Detection – A Comparative Analysis of 4 Machine Learning Models

This article was published as a part of the Data Science Blogathon Introduction This article aims to compare four different deep learning and machine learning algorithms to build a spam detector and evaluate their performances. The dataset we used was from a shuffled sample of email subjects and bodies containing both spam and ham emails in numerous proportions, which we converted into lemmas. Email Spam Detection is one of the most effective projects of Deep learning but this is often also […]

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Performing Sentiment Analysis Using Twitter Data!

Photo by Daddy Mohlala on Unsplash Data is water, purifying to make it edible is a role of Data Analyst – Kashish Rastogi We are going to clean the twitter text data and visualize data in this blog. Table Of Contents: Problem Statement Data Description Cleaning text with NLP Finding if the text has: with spacy Cleaning text with preprocessor library Analysis of the sentiment of data Data visualizing   I am taking the twitter data which is available here on […]

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Getting Started with Natural Language Processing using Python

This article was published as a part of the Data Science Blogathon Why NLP? Natural Language Processing has always been a key tenet of Artificial Intelligence (AI). With the increase in the adoption of AI, systems to automate sophisticated tasks are being built. Some of these examples are described below. Diagnosing rare form of cancer –  At the University of Tokyo’s Institute of Medical Science, doctors used artificial intelligence to successfully diagnose a rare type of leukemia. The doctors used an AI […]

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Indexing in Natural Language Processing for Information Retrieval

This article was published as a part of the Data Science Blogathon Overview This blog covers GREP(Global-Regular-Expression-Print) and its drawbacks Then we move on to Document Term Matrix and Inverted Matrix Finally, we end with dynamic and distributed indexing image source-https://javarevisited.blogspot.com/2011/06/10-examples-of-grep-command-in-unix-and.html#axzz6zwakOXgt     Global Regular Expression Print Whenever we are dealing with a small amount of data, we can use the grep command very efficiently. It allows us to search one or more files for lines that contain a pattern. For […]

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Let’s Understand How does a chatbot work ?

Introduction A technology that makes the interaction between humans and machines in natural language possible, is an Artificial Intelligence Chatbot! They act like a typical search engine but with more enhanced features. Applications of Artificial Intelligence Chatbots are spread over various domains including eCommerce, healthcare, education, travel, automation, finance, hospitality, insurance, and so on. The chatbots are domain-specific and do what they are intended for.  The applications in their domain include: answering customer queries, booking services like flights, movie tickets, […]

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