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    Natural Language Processing with Python: Natural Language Processing Using NLTK
    Natural Language Processing with Python: Natural Language Processing Using NLTK
    Natural Language Processing with Python: Natural Language Processing Using NLTK
    Ebook71 pages1 hour

    Natural Language Processing with Python: Natural Language Processing Using NLTK

    By Frank Millstein

    3.5/5

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    About this ebook

    This book is a perfect beginner's guide to natural language processing. It is offering an easy to understand guide to implementing NLP techniques using Python. Natural language processing has been around for more than fifty years, but just recently with greater amounts of data present and better computational powers, it has gained a greater popularity.

    Given the importance of data, there is no wonder why natural language processing is on the rise. If you are interested in learning more, this book will serve as your best companion on this journey introducing you to this challenging, yet extremely engaging world of automatic manipulation of our human language.

    It covers all the basics you need to know before you dive deeper into NLP and solving more complex NLP tasks in Python.

    Here Is a Preview of What You'll Learn Here…

    • The main challenges of natural language processing
    • The history of natural language processing
    • How natural langauge processing actually works
    • The main natural language processing applications
    • Text preprocessing and noise removal
    • Feature engineering and syntactic parsing
    • Part of speech tagging and named entity extraction
    • Topic modeling and word embedding
    • Text classification problems
    • Working with text data using NLTK
    • Text summarization and sentiment analysis
    • And much, much more...

    Get this book NOW and learn more about Natural Language Processing With Python!

    LanguageEnglish
    PublisherFrank Millstein
    Release dateOct 19, 2019
    ISBN9781393688297
    Natural Language Processing with Python: Natural Language Processing Using NLTK

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    Reviews for Natural Language Processing with Python

    3.5/5

    4 ratings4 reviews

    What our readers think

    Readers find this title frustrating due to typos and lack of formatting, but overall it is a good book for beginners to easily understand NLP. Some readers feel that the content is shallow and lacks depth, wishing for a more intuitive explanation of NLP methods. However, the book provides a better understanding of NLP analysis."

    What did you think?

    Tap to rate

    Review must be at least 10 words

    • 5/5
      Absolutely very good book for beginners ,very easy to read and understand
    • 1/5
      The content of this book is too shallow. It does not go into depth at all, only breadth. I would appreciate it if the author provided a more intuitive explanation to understand what NLP is and why we use the methods we use today to analyse to do NLP analysis.
    • 5/5
      a good book to read and after studying the book we will know better about nlp
    • 3/5
      The sheer number of typos and lack of formatting was frustrating.

    Book preview

    Natural Language Processing with Python - Frank Millstein

    By Frank Millstein

    WHAT IS IN THE BOOK?

    INTRODUCTION

    CHALLENGES OF NATURAL LANGUAGE PROCESSING

    HISTORY OF NATURAL LANGUAGE PROCESSING

    GROWING IMPORTANCE OF NATURAL LANGUAGE PROCESSING

    HOW NATURAL LANGUAGE PROCESSING WORKS?

    NATURAL LANGUAGE PROCESSING APPLICATIONS

    CHAPTER 1: TEXT PREPROCESSING

    NOISE REMOVAL

    CHAPTER 2: FEATURE ENGINEERING

    SYNTACTIC PARSING

    PART OF SPEECH TAGGING

    ENTITY EXTRACTION

    TOPIC MODELING

    N-GRAMS

    TEXT DATA STATISTICAL FEATURES

    WORD EMBEDDING

    CHAPTER 3: TEXT CLASSIFICATION

    TEXT MATCHING

    LEVENSHTEIN DISTANCE

    PHONETIC MATCHING

    FLEXIBLE STRING MATCHING

    COREFERENCE RESOLUTION

    CHAPTER 4: WORKING WITH LANGUAGE DATA USING NLTK

    IMPORTING NLTK

    DOWNLOADING NLTK’S TAGGER AND DATA

    TOKENIZING SENTENCES

    TAGGING SENTENCES

    COUNTING PART OF SPEECH TAGS

    RUNNING NATURAL LANGUAGE PROCESSING SCRIPT

    CHAPTER 5: TEXT SUMMARIZATION

    REMOVING STOP-WORDS

    ASSIGNING SCORES TO SENTENCES

    FREQUENCY TABLE ENHANCEMENT

    CHAPTER 6: SENTIMENT ANALYSIS

    LOADING NTLK PACKAGES

    CLEANING TEXT DATA

    EXTRACTING FEATURES

    CHAPTER 7: STEMMING AND LEMMATIZATION

    STEMMING NON-ENGLISH WORDS

    GETTING SYNONYMS AND ANTONYMS FROM WORDNET

    LAST WORDS

    Copyright © 2018 by Frank Millstein- All rights reserved.

    This document is geared towards providing exact and reliable information in regards to the topic and issue covered. The publication is sold with the idea that the publisher is not required to render accounting, officially permitted, or otherwise, qualified services. If advice is necessary, legal or professional, a practiced individual in the profession should be ordered.

    From a Declaration of Principles which was accepted and approved equally by a Committee of the American Bar Association and a Committee of Publishers and Associations.

    In no way is it legal to reproduce, duplicate, or transmit any part of this document by either electronic means or in printed format. Recording of this publication is strictly prohibited, and any storage of this document is not allowed unless with written permission from the publisher. All rights reserved.

    The information provided herein is stated to be truthful and consistent, in which any liability, in terms of inattention or otherwise, by any usage or abuse of any policies, processes, or directions contained within is the solitary and utter responsibility of the recipient reader. Under no circumstances will any legal responsibility or blame be held against the publisher for any reparation, damages, or monetary loss due to the information herein, either directly or indirectly.

    Respective authors own all copyrights not held by the publisher.

    The information herein is offered for informational purposes solely and is universal as so. The presentation of the information is without contract or any type of guarantee assurance.

    The trademarks that are used are without any consent, and the publication of the trademark is without permission or backing by the trademark owner. All trademarks and brands within this book are for clarifying purposes only and are owned by the owners themselves, not affiliated with this document.

    INTRODUCTION

    As we are going to extensively explore here in this book, natural language processing is a broad field of artificial intelligence which is focused on finding interactions between computer and human language. In fact, natural language processing sits at the intersection of three different studies including computational linguistics, artificial intelligence, and computer science.

    NLP, as we also call natural language processing, is a wide-ranging field which covers manipulation and computer understanding of human language. You will usually hear about NLP in context of analyzing large pools of document sets or legislation where people are attempting to discover patterns which suggest corruption and other inconsistencies.

    In fact, NLP is the amazing ability of computer programs to understand spoken human language, and thus, the far-reaching field of artificial intelligence. The development of NLP applications is very challenging as computers and machines require humans to speak to them in numerous programming languages which is highly structured and precise through voice commands.

    However, as you know, human speech is not always so precise, and human speech linguistic structure frequently depends on various complex variables such as social context, regional dialect or slang.

    Therefore, natural language practice generally comes across many challenges when it comes to interpreting spoken human language. Today, NLP as a branch of artificial intelligence is of amazing importance to our data science research, computer science and deep learning as it helps machines or computers to understand, then interpret and finally manipulate human language with great success. Therefore, NLP draws together many other disciplines such as computational linguistics and computer science to bridge those gaps between computer understanding and human communication.

    Natural language processing can broadly be defined as the automatic interpretation

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