Natural Language Processing with Python

Analyzing Text with the Natural Language Toolkit
Author: Steven Bird,Ewan Klein,Edward Loper
Publisher: "O'Reilly Media, Inc."
ISBN: 0596555717
Category: Computers
Page: 504
View: 9115

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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 translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

Theorie, Semantik und Organisation von Wissen


Author: Wieslaw Babik,H. Peter Ohly,Karsten Weber
Publisher: Ergon Verlag
ISBN: 3956503260
Category: Social Science
Page: 446
View: 5436

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Proceedings der 13. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und dem 13. Internationalen Symposium der Informationswissenschaft der Higher Education Association for Information Science (HI) Potsdam (19.–20.03.2013): 'Theory, Information and Organization of Knowledge' | Proceedings der 14. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und Natural Language & Information Systems (NLDB) Passau (16.06.2015): 'Lexical Resources for Knowledge Organization' | Proceedings des Workshops der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) auf der SEMANTICS Leipzig (1.09.2014): 'Knowledge Organization and Semantic Web' | Proceedings des Workshops der Polnischen und Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) Cottbus (29.–30.09.2011): 'Economics of Knowledge Production and Organization'

Natural Language Processing with PyTorch

Build Intelligent Language Applications Using Deep Learning
Author: Delip Rao,Brian McMahan
Publisher: "O'Reilly Media, Inc."
ISBN: 149197818X
Category: Computers
Page: 256
View: 5766

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Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

Advances in Natural Language Processing

9th International Conference on NLP, PolTAL 2014, Warsaw, Poland, September 17-19, 2014. Proceedings
Author: Adam Przepiórkowski,Maciej Ogrodniczuk
Publisher: Springer
ISBN: 3319108883
Category: Computers
Page: 492
View: 9795

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This book constitutes the refereed proceedings of the 9th International Conference on Advances in Natural Language Processing, PolTAL 2014, Warsaw, Poland, in September 2014. The 27 revised full papers and 20 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on morphology, named entity recognition, term extraction; lexical semantics; sentence level syntax, semantics, and machine translation; discourse, coreference resolution, automatic summarization, and question answering; text classification, information extraction and information retrieval; and speech processing, language modelling, and spell- and grammar-checking.

Sprachverarbeitung

Grundlagen und Methoden der Sprachsynthese und Spracherkennung
Author: Beat Pfister,Tobias Kaufmann
Publisher: Springer-Verlag
ISBN: 366252838X
Category: Computers
Page: 507
View: 2230

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Das Buch erklärt die wesentlichen Ansätze zur Sprachsynthese und zur Spracherkennung und vermittelt die dafür relevanten Grundlagen. Dazu gehören insbesondere: Grundkenntnisse über die menschliche Sprachproduktion und Sprachwahrnehmung Eigenschaften von Sprachsignalen und ihre Darstellung Grundkenntnisse in Linguistik, insbes. Phonetik, Morphologie und Syntax die wichtigsten Transformationen und Methoden der digitalen Sprachsignalverarbeitung statistische Ansätze zur Beschreibung vieldimensionaler Größen und komplexer Zusammenhänge (Hidden-Markov-Modelle und neuronale Netze) Formulierung und Anwendung von Wissen in der Form von Regeln Die 2. Auflage des Buches enthält ein neues Kapitel über die polyglotte Sprachsynthese, die gemischtsprachigen Text korrekt vorlesen kann. Zusätzlich werden sowohl für die Sprachsignalproduktion als auch für die Spracherkennung die neusten Ansätze eingeführt.Die ZielgruppenDieses gut lesbare Buch wendet sich insbesondere an Studierende im Bereich Sprachverarbeitung. Das Buch geht auch auf viele praktische Probleme ein, die beim Konzipieren von sprachverarbeitenden Systemen zu lösen sind. Ein ausführliches Glossar und eine Internet-basierte Sammlung von Hörbeispielen, Illustrationen und Übungen ergänzen das Buch.

Python kurz & gut


Author: Mark Lutz
Publisher: O'Reilly Germany
ISBN: 3955617718
Category: Computers
Page: 280
View: 7346

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Die objektorientierte Sprache Python eignet sich hervorragend zum Schreiben von Skripten, Programmen und Prototypen. Sie ist frei verfügbar, leicht zu lernen und zwischen allen wichtigen Plattformen portabel, einschließlich Linux, Unix, Windows und Mac OS. Damit Sie im Programmieralltag immer den Überblick behalten, sind die verschiedenen Sprachmerkmale und Elemente in Python – kurz & gut übersichtlich zusammengestellt. Für Auflage 5 wurde die Referenz komplett überarbeitet, erweitert und auf den neuesten Stand gebracht, so dass sie die beiden aktuellen Versionen 2.7 und 3.4 berücksichtigt. Python – kurz & gut behandelt unter anderem: Eingebaute Typen wie Zahlen, Listen, Dictionarys u.v.a.; nweisungen und Syntax für Entwicklung und Ausführung von Objekten; Die objektorientierten Entwicklungstools in Python; Eingebaute Funktionen, Ausnahmen und Attribute; pezielle Methoden zur Operatorenüberladung; Weithin benutzte Standardbibliotheksmodule und Erweiterungen; Kommandozeilenoptionen und Entwicklungswerkzeuge. Mark Lutz stieg 1992 in die Python-Szene ein und ist seitdem als aktiver Pythonista bekannt. Er gibt Kurse, hat zahlreiche Bücher geschrieben und mehrere Python-Systeme programmiert.

Automatic Text Summarization


Author: Juan-Manuel Torres-Moreno
Publisher: John Wiley & Sons
ISBN: 1119044073
Category: Computers
Page: 320
View: 7728

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Textual information in the form of digital documents quickly accumulates to create huge amounts of data. The majority of these documents are unstructured: it is unrestricted text and has not been organized into traditional databases. Processing documents is therefore a perfunctory task, mostly due to a lack of standards. It has thus become extremely difficult to implement automatic text analysis tasks. Automatic Text Summarization (ATS), by condensing the text while maintaining relevant information, can help to process this ever-increasing, difficult-to-handle, mass of information. This book examines the motivations and different algorithms for ATS. The author presents the recent state of the art before describing the main problems of ATS, as well as the difficulties and solutions provided by the community. The book provides recent advances in ATS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several examples are also included in order to clarify the theoretical concepts.

Grundlagen der Computerlinguistik

Mensch-Maschine-Kommunikation in natürlicher Sprache
Author: Roland R. Hausser
Publisher: Springer-Verlag
ISBN: 3642573061
Category: Computers
Page: 572
View: 2572

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Die zentrale Aufgabe einer zukunftsorientierten Computerlinguistik ist die Entwicklung kognitiver Maschinen, mit denen Menschen in ihrer jeweiligen Sprache frei reden können. Langfristig umfaßt diese Zielsetzung eine funktional ausgerichtete Theoriebildung, eine objektive Verifikationsmethode und eine Fülle praktischer Anwendungen. Für die natürlichsprachliche Kommunikation wird nicht nur Sprachverarbeitung, sondern auch nichtsprachliche Wahrnehmung und Handlung benötigt. Deshalb ist der Inhalt dieses Lehrbuchs als Sprachtheorie für die Konstruktion sprechender Roboter organisiert. Sein zentrales Thema ist die Kommunikationsmechanik natürlicher Sprachen - beim Sprecher und beim Hörer. Der Inhalt ist in folgende vier Teile mit je sechs Kapiteln gegliedert: Sprachtheorie; Formale Grammatik; Morphologie und Syntax; Semantik und Pragmatik. Insgesamt 772 Übungsaufgaben dienen der Verständniskontrolle und -vertiefung.

Modeling Techniques in Predictive Analytics with Python and R

A Guide to Data Science
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 013389214X
Category: Computers
Page: 448
View: 4261

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Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Text Analytics with Python

A Practical Real-World Approach to Gaining Actionable Insights from your Data
Author: Dipanjan Sarkar
Publisher: Apress
ISBN: 1484223888
Category: Computers
Page: 385
View: 6785

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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 techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Programmieren lernen

Eine grundlegende Einführung mit Java
Author: Peter Pepper
Publisher: Springer-Verlag
ISBN: 3540327827
Category: Computers
Page: 488
View: 2894

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Objektorientiertes Programmieren mittels Java: Dieses Lehrbuch liefert sicher und systematisch die grundlegenden Kenntnisse dazu. Im weiteren Verlauf behandelt es u.a. folgende Themen: Objekte und (generische) Klassen, Kontrollanweisungen und Datenstrukturen, wichtige Algorithmen zum Suchen und Sortieren von Daten sowie für einfache numerische Anwendungen und elementare Graph-Traversierung. Modularisierungskonzepte und Methoden der nebenläufigen Programmierung mittels Threads, des Exception-Handlings, der Ein- und Ausgabe sowie von grafischen Benutzerschnittstellen runden das Buch ab. Systematisch und für vielfältige Anwendungen geeignet.

Web and Network Data Science

Modeling Techniques in Predictive Analytics
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133887642
Category: Computers
Page: 384
View: 4472

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Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Modeling Techniques in Predictive Analytics

Business Problems and Solutions with R, Revised and Expanded Edition
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133886190
Category: Computers
Page: 384
View: 5420

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To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Einführung in TensorFlow

Deep-Learning-Systeme programmieren, trainieren, skalieren und deployen
Author: Tom Hope,Yehezkel S. Resheff,Itay Lieder
Publisher: O'Reilly
ISBN: 3960101813
Category: Computers
Page: 238
View: 1105

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Deep-Learning-Netze, die mit großen Datenmengen angelernt wurden, lösen komplexe Aufgaben mit erstaunlicher Genauigkeit. TensorFlow ist die führende Open-Source-Bibliothek zum Erstellen und Trainieren neuronaler Deep-Learning-Netze z.B. für die Sprach- und Bilderkennung, die Verarbeitung natürlicher Sprache (NLP) oder die vorhersagende Datenanalyse. Dieses Buch bietet einer breiten technisch orientierten Leserschaft einen praxisnahen Zugang zu den Grundlagen von TensorFlow.Sie erarbeiten zunächst einige einfache Beispielaufgaben mit TensorFlow und tauchen anschließend tiefer in Themen ein wie die Architektur neuronaler Netze, die Visualisierung mit TensorBoard, Abstraktionsbibliotheken für TensorFlow oder Multithread-Pipelines zur Dateneingabe. Wenn Sie dieses Buch durchgearbeitet haben, sind Sie in der Lage, Deep-Learning-Systeme mit TensorFlow zu erstellen und im Produktivbetrieb einzusetzen.

Java

Eine Einführung in die Programmierung
Author: Dirk Louis,Peter Müller
Publisher: Carl Hanser Verlag GmbH Co KG
ISBN: 3446457267
Category: Computers
Page: 450
View: 3170

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Der Java-Klassiker im neuen Gewand! Steigen Sie ein in die faszinierende Welt der Java-Programmierung und lernen Sie, wie Sie Ihre Ideen Schritt für Schritt umsetzen. Hier lernen Sie, wie Sie mit Java programmieren und - wie Sie Ihre Entwicklungsumgebung richtig einrichten, - wie Sie Ihren Programmquelltext sinnvoll organisieren, - wie Sie objektorientiert programmieren, - wie Sie Java-Programme mit grafischen Benutzeroberflächen aus Fenstern, Dialogen, Steuerelementen und Menüs schreiben, - wie Sie einen eigenen Texteditor, ein Malprogramm, einen Bildbetrachter oder andere typische Programme schreiben können, - wie Sie von Java-Programmen aus auf die Daten in einer Datenbank zugreifen. Mit vielen Beispielen und Übungen und behandelt auch Grafik, Datenbanken und Threads Die Mischung macht ́s! Lernen Sie mit einfachen didaktischen, nützlichen und unterhaltsamen Programmen. Erzeugen Sie individuelle, interaktive Oberflächen. Lassen Sie sich zu eigenen Ideen anregen! Inklusive vollständige Software-Ausstattung auf der Buch-DVD...

Die Verwandlung


Author: Franz Kafka
Publisher: SEVERUS Verlag
ISBN: 3958019587
Category: Fiction
Page: 80
View: 9663

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»Als Gregor Samsa eines morgens aus unruhigen Träumen erwachte, fand er sich in seinem Bett zu einem ungeheueren Ungeziefer verwandelt.« Und als er feststellt, dass es sich nicht um einen Alptraum handelt, nimmt das Schicksal seinen Lauf. Trotz seines friedfertigen und unschuldigen Lebens als Ungeziefer wird er von seiner Familie verstoßen und schließlich in den Tod getrieben. „Die Verwandlung“ ist bis heute die vielleicht bekannteste und vielschichtigste von Kafkas Erzählungen. Wie kaum ein anderes Stück Literatur hat ›Die Verwandlung‹ die Leser zugleich begeistert, verstört und zu verschiedensten Deutungen angeregt.

Natural Language Processing Fundamentals

Build intelligent applications that can interpret the human language to deliver impactful results
Author: Sohom Ghosh,Dwight Gunning
Publisher: Packt Publishing Ltd
ISBN: 178995598X
Category: Computers
Page: 374
View: 9540

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Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key Features Assimilate key NLP concepts and terminologies Explore popular NLP tools and techniques Gain practical experience using NLP in application code Book Description If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language. What you will learn Obtain, verify, and clean data before transforming it into a correct format for use Perform data analysis and machine learning tasks using Python Understand the basics of computational linguistics Build models for general natural language processing tasks Evaluate the performance of a model with the right metrics Visualize, quantify, and perform exploratory analysis from any text data Who this book is for Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.