Tag: Natural Language Processing

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Using Linguistic Features in NLP

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If you had to describe what NLP is about, what would you point out as the most important thing? Is there something that is vital for many use cases and is employed in almost every NLP application? For example, what do you almost certainly need when it comes to a task of information extraction of any kind? Right. Linguistic features,...

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Intelligent Text Generation with spaCy Part1

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The most challenging tasks in natural language processing are natural language understanding and natural language generation. This article focuses on the latter, giving an example of how you might teach your conversational application to respond properly to its users. Of course, you will not find here a universal solution that covers all possible cases and can be implemented with just...

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Using Linguistic Features in NLP

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If you had to describe what NLP is about, what would you point out as the most important thing? Is there something that is vital for many use cases and is employed in almost every NLP application? For example, what do you almost certainly need when it comes to a task of information extraction of any kind? Right. Linguistic features,...

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Quick Start with spaCy

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Natural language processing (NLP) is one of the most interesting, yet challenging fields of artificial intelligence (AI). spaCy is the leading Python library for NLP, gaining popularity rapidly. Let’s take a closer look at spaCy, trying to figure out how it can be useful for accomplishing NLP tasks. What Is spaCy? spaCy is an open-source Python library for performing NLP...

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What Computational Linguistic Is About

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To this point, humanity has a huge amount of data that can be used to automate many repeatable tasks, thus allowing us, humans to switch to more interesting work. One approach to take advantage of large amounts of data – which has become very popular recently – is based on using machine learning algorithms. This is when a machine is...

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Converting Raw Text into SQL Data with spaCy

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As the title suggests, this article covers how raw text can be converted into structured data. Before going any further, a word on the terminology used here is needed. In simple terms, raw text can be thought of as a set of tokens grouped into sentences, carrying information expressed in a natural language such as English. Put simply, raw text...

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Training Models in spaCy

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spaCy v2.0 features statistical neural network models for named entity recognition, dependency parsing, and similarity prediction. One of the most exciting opportunities is that you cannot only use pre-trained, ready-for-use models, but you can also train a model with your own training examples, thus tuning it for your particular use case. spaCy’s Model Architecture Before starting to train a model,...

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Intelligent Text Processing with spaCy

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The task of extracting meaning from text data can be quite challenging. The problem is that you cannot rely on the meaning of individual words in a sentence or phrase, since the order of words may invert the whole point. Moreover, the same words may have different meaning, depending on the context. To address this problem, NLP has linguistic features...

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