Applied Text Analysis with Python Book [PDF] Download

Download the fantastic book titled Applied Text Analysis with Python written by Benjamin Bengfort, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Applied Text Analysis with Python", which was released on 11 June 2018. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Applied Text Analysis with Python by Benjamin Bengfort 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


Detail About Applied Text Analysis with Python PDF

  • Author : Benjamin Bengfort
  • Publisher : "O'Reilly Media, Inc."
  • Genre : Computers
  • Total Pages : 332 pages
  • ISBN : 1491962992
  • PDF File Size : 45,7 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Applied Text Analysis with Python

Applied Text Analysis with Python
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 24,6 Mb
  • Release Date : 11 June 2018
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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

Text Analytics with Python

Text Analytics with Python
  • Publisher : Apress
  • File Size : 22,5 Mb
  • Release Date : 30 November 2016
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Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and

Text Analytics with Python

Text Analytics with Python
  • Publisher : Apress
  • File Size : 25,7 Mb
  • Release Date : 21 May 2019
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Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp

Blueprints for Text Analytics Using Python

Blueprints for Text Analytics Using Python
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 51,7 Mb
  • Release Date : 04 December 2020
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Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving

Natural Language Processing with Python

Natural Language Processing with Python
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 31,6 Mb
  • Release Date : 12 June 2009
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This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and

Applied Data Science with Python and Jupyter

Applied Data Science with Python and Jupyter
  • Publisher : Packt Publishing Ltd
  • File Size : 47,5 Mb
  • Release Date : 31 October 2018
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Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications. Key FeaturesGet up and running with the Jupyter ecosystem and

Applied Natural Language Processing with Python

Applied Natural Language Processing with Python
  • Publisher : Apress
  • File Size : 37,8 Mb
  • Release Date : 11 September 2018
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Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will

Text Mining with R

Text Mining with R
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 29,6 Mb
  • Release Date : 12 June 2017
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Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining

An Introduction to Statistical Learning

An Introduction to Statistical Learning
  • Publisher : Springer Nature
  • File Size : 39,7 Mb
  • Release Date : 01 August 2023
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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have

Python Data Science Handbook

Python Data Science Handbook
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 32,5 Mb
  • Release Date : 21 November 2016
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For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data