Applied Text Analysis with Python By Benjamin Bengfort, Rebecca Bilbro & Tony Oj

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“Paperback book in excellent condition the pages are unmarked - no highlighting or writing”
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Item specifics

Condition
Like New
A book that looks new but has been read. Cover has no visible wear, and the dust jacket (if applicable) is included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See the seller’s listing for full details and description of any imperfections. See all condition definitionsopens in a new window or tab
Seller Notes
“Paperback book in excellent condition the pages are unmarked - no highlighting or writing”
Book Title
APPLIED TEXT ANALYSIS WITH PYTHON
ISBN
9781491963043
Subject Area
Computers
Publication Name
Applied Text Analysis with Python : Enabling Language-Aware DATAPRODUCTS with Machine Learning
Publisher
O'reilly Media, Incorporated
Item Length
9.3 in
Subject
Data Modeling & Design, Natural Language Processing, Data Processing, Databases / General, Programming Languages / Python
Publication Year
2018
Type
Textbook
Format
Trade Paperback
Language
English
Item Height
0.7 in
Author
Tony Ojeda, Rebecca Bilbro, Benjamin Bengfort
Item Weight
19.8 Oz
Item Width
7.1 in
Number of Pages
350 Pages
Category

About this product

Product Identifiers

Publisher
O'reilly Media, Incorporated
ISBN-10
1491963042
ISBN-13
9781491963043
eBay Product ID (ePID)
236664284

Product Key Features

Number of Pages
350 Pages
Publication Name
Applied Text Analysis with Python : Enabling Language-Aware DATAPRODUCTS with Machine Learning
Language
English
Publication Year
2018
Subject
Data Modeling & Design, Natural Language Processing, Data Processing, Databases / General, Programming Languages / Python
Type
Textbook
Author
Tony Ojeda, Rebecca Bilbro, Benjamin Bengfort
Subject Area
Computers
Format
Trade Paperback

Dimensions

Item Height
0.7 in
Item Weight
19.8 Oz
Item Length
9.3 in
Item Width
7.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2018-276483
Illustrated
Yes
Synopsis
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
LC Classification Number
QA76.9.N38

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denzbunch6kzm

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  • by diga4964
    Apr 21, 2024

    Better than expected. Was in great condition

    Better than expected. Was in great condition

    Verified purchase: YesCondition: Pre-OwnedSold by: second.sale

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