Applied text analysis with Python enabling language-aware data products with machine learning

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data source...

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Bibliographic Details
Main Authors: Bengfort, Benjamin, Bilbro, Rebecca (Author), Ojeda, Tony (Author)
Format: eBook
Language:English
Published: Sebastopol, CA O'Reilly Media 2018
Edition:First edition
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist's approach to building language-aware products with applied machine learning. You'll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you'll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations. Perform document classification and topic modeling. Steer the model selection process with visual diagnostics. Extract key phrases, named entities, and graph structures to reason about data in text. Build a dialog framework to enable chatbots and language-driven interaction. Use Spark to scale processing power and neural networks to scale model complexity.--Provided by publisher
Physical Description:xviii, 310 pages illustrations
ISBN:1491963042
9781491963043
9781491962992
1491963018
9781491963012
1491962992