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Using Linguistic Features in NLP

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

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

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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Parsing Intents and Their Targets into SQL Queries with spaCy: Part 2

In the previous article of this series, you learned that spaCy allows you to train its parser to be specific to your domain, which can be useful if you, for example, are developing a conversational application. In the example given in the article, you were guided through the steps of preparing training examples for the parser and then training the...

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Parsing Intents and Their Targets into SQL Queries with spaCy: Part 1

People use natural languages to communicate with each other. To efficiently interact with a machine, good knowledge of programming languages is required. Natural Language Processing (NLP) is here to enable human-machine communications through natural languages. This is however, a very general notion of what NLP is. Intuitively, it may seem that an NLP-enabled application understands human speech natively, like a...

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Training Models in spaCy

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

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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