eBook Applied Text Analysis With Python - Enabling Language Aware Data Products With Machine Learning by Benjamin Bengfort Full [PDF ePUB Audiobook]

Free download and read ebooks online Applied Text Analysis With Python - Enabling Language Aware Data Products With Machine Learning by Benjamin Bengfort, Tony Ojeda, Rebecca Bilbro full book PDF ePUB Audiobook. Download a free ebooks and kindle audiobook Applied Text Analysis With Python - Enabling Language Aware Data Products With Machine Learning with ISBN id 9781491963043 full page with book summary. Benjamin Bengfort book PDF ePUB of Applied Text Analysis With Python - Enabling Language Aware Data Products With Machine Learning published by O'Reilly Media in 2018-06-22. Applied Text Analysis with Python released with category Computers with total 310 pages.

Applied Text Analysis With Python - Enabling Language Aware Data Products With Machine Learning
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Applied Text Analysis With Python - Enabling Language Aware Data Products With Machine Learning by Benjamin Bengfort free book pdf

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

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