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Event extraction is the process of identifying and extracting important events from textual information such as news articles, reports, and social media posts. It is a significant task in natural language processing (NLP), as it can help analysts to gather important insights from a large amount of text. However, it is not an easy task,…
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Text classification involves dividing text data into different classes or categories based on their content and context. Machine learning and natural language processing techniques are used to develop and train text classification models. These models are essential in various applications, including social media monitoring, email services, e-commerce websites, media outlets, and translation software. Text classification…
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Machine learning is a rapidly growing field of artificial intelligence that involves the use of algorithms and statistical models to allow machines to learn from data and improve their performance over time without being explicitly programmed. This article aims to provide a beginner’s guide to help those who are new to the subject understand the…
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Aspect-based sentiment analysis has emerged as a powerful tool for businesses to derive meaningful insights from customer feedback. It involves analyzing the sentiment towards specific aspects of a product, service, or brand, instead of looking at the overall sentiment. This approach provides a more nuanced understanding of customer opinions and preferences, allowing companies to make…
Natural Language Processing (NLP) is a game-changing technology that helps machines comprehend and interpret human language. NLP has come a long way in recent years, and it’s vital to explore the current state of advancements and the challenges it faces in the future. The field of NLP utilizes machine learning and deep learning techniques, which…
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Deep learning is a powerful form of machine learning that has transformed the artificial intelligence landscape. At the heart of deep learning are neural networks, which are inspired by the way the human brain processes information. These networks are capable of learning and making decisions based on complex input data, making them incredibly useful for…
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Coreference resolution plays a crucial role in natural language processing (NLP). It is a process of identifying all the pronouns present in a text and linking them with the correct noun they represent. This task may seem simple, but it is quite challenging due to ambiguity and references that span over multiple sentences. Failure to…
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Language generation models are a branch of artificial intelligence that uses deep learning algorithms to generate text that closely resembles human language. These models have a wide range of applications, including chatbots, language translation, and content creation. One of the most exciting applications of language generation models is in chatbots. These models help chatbots engage…
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Natural Language Processing (NLP) is a subfield of Artificial Intelligence that focuses on how humans interact with computers and machines can comprehend and respond suitably to human language. It involves the use of computational and mathematical techniques to process, analyze, and understand extensive language data. NLP has made it possible for computers to comprehend, interpret,…
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Natural Language Processing (NLP) relies heavily on text data that is clean and formatted in a manner that allows for efficient analysis. That’s why text preprocessing techniques are essential for NLP. There are several techniques that one can employ to clean and format text data. The first and most important technique is tokenization. Tokenization involves…
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