Author: Yuli Vasiliev

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Intelligent Text Generation with spaCy Part3

In this part, we’ll discuss how to convert questions into statements or vice versa. As you know, in English word order in questions differs from word order in statements. You already saw a simple example of translating a question into a statement in part 1 of this article series. In this article, we’ll take a closer look at this problem,…...

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Intelligent Text Generation with spaCy Part2

Word sequence patterns based on linguistic features and introduced in the previous article in this series are not the only means of intelligent text processing and text generation. This article focuses on another common technique based on using syntactic dependency trees. This is also one of those techniques that you can use to teach your conversational application to generate meaningful…...

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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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Intelligent Text Generation with spaCy Part1

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

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 spaCy’s Parser for Conversational Applications

If you already have some experience with spaCy, you know that there are a lot of pre-trained statistical models that can be put in use immediately. These models are not trained however to work in certain areas. In other words, they may not be specific to your domain. This may push you to consider improving an existing model or creating…...

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