Tag: Deep Learning

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

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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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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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