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Introduction To Spacy


Introduction To Spacy
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Natural Language Processing With Python And Spacy


Natural Language Processing With Python And Spacy
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Author : Yuli Vasiliev
language : en
Publisher: No Starch Press
Release Date : 2020-04-28

Natural Language Processing With Python And Spacy written by Yuli Vasiliev and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-28 with Computers categories.


An introduction to natural language processing with Python using spaCy, a leading Python natural language processing library. Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You'll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You'll even learn how to transform statements into questions to keep a conversation going. You'll also learn how to: • Work with word vectors to mathematically find words with similar meanings (Chapter 5) • Identify patterns within data using spaCy's built-in displaCy visualizer (Chapter 7) • Automatically extract keywords from user input and store them in a relational database (Chapter 9) • Deploy a chatbot app to interact with users over the internet (Chapter 11) "Try This" sections in each chapter encourage you to practice what you've learned by expanding the book's example scripts to handle a wider range of inputs, add error handling, and build professional-quality applications. By the end of the book, you'll be creating your own NLP applications with Python and spaCy.



Practical Natural Language Processing


Practical Natural Language Processing
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Author : Sowmya Vajjala
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-17

Practical Natural Language Processing written by Sowmya Vajjala and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-17 with Computers categories.


Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective



Applied Natural Language Processing In The Enterprise


Applied Natural Language Processing In The Enterprise
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Author : Ankur A. Patel
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-12

Applied Natural Language Processing In The Enterprise written by Ankur A. Patel and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-12 with Computers categories.


NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production



Natural Language Processing With Python


Natural Language Processing With Python
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Author : Steven Bird
language : en
Publisher:
Release Date : 2009

Natural Language Processing With Python written by Steven Bird and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.


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.



Natural Language Processing With Pytorch


Natural Language Processing With Pytorch
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Author : Delip Rao
language : en
Publisher: O'Reilly Media
Release Date : 2019-01-22

Natural Language Processing With Pytorch written by Delip Rao and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-22 with Computers categories.


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



Python Natural Language Processing


Python Natural Language Processing
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Author : Jalaj Thanaki
language : en
Publisher:
Release Date : 2017-07-31

Python Natural Language Processing written by Jalaj Thanaki and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-31 with Machine learning categories.


Leverage the power of machine learning and deep learning to extract information from text dataAbout This Book* Implement Machine Learning and Deep Learning techniques for efficient natural language processing* Get started with NLTK and implement NLP in your applications with ease* Understand and interpret human languages with the power of text analysis via PythonWho This Book Is ForThis book is intended for Python developers who wish to start with natural language processing and want to make their applications smarter by implementing NLP in them.What You Will Learn* Focus on Python programming paradigms, which are used to develop NLP applications* Understand corpus analysis and different types of data attribute.* Learn NLP using Python libraries such as NLTK, Polyglot, SpaCy, Standford CoreNLP and so on* Learn about Features Extraction and Feature selection as part of Features Engineering.* Explore the advantages of vectorization in Deep Learning.* Get a better understanding of the architecture of a rule-based system.* Optimize and fine-tune Supervised and Unsupervised Machine Learning algorithms for NLP problems.* Identify Deep Learning techniques for Natural Language Processing and Natural Language Generation problems.In DetailThis book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them.During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis.You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data.By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world.Style and approachThis book teaches the readers various aspects of natural language Processing using NLTK. It takes the reader from the basic to advance level in a smooth way.



Natural Language Processing And Computational Linguistics


Natural Language Processing And Computational Linguistics
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Author : Bhargav Srinivasa-Desikan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-29

Natural Language Processing And Computational Linguistics written by Bhargav Srinivasa-Desikan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-29 with Computers categories.


Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!



Introduction To Spacy


Introduction To Spacy
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Author :
language : en
Publisher: shyambhu mukherjee
Release Date : 2023-12-21

Introduction To Spacy written by and has been published by shyambhu mukherjee this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-21 with Computers categories.


This is a short book that aims to introduce a data science enthusiast to the cutting-edge nlp tool called spacy. The chapters are compiled from my blog which got really famous when I gradually published the articles. In this book, all those articles are combined into one summarized book which takes you through the basics to the advanced of the spacy language. Extensive examples of codes and error resolving are included as well. One should expect a industry level working knowledge of spacy upon completing this book.



Introduction To Machine Learning With Python


Introduction To Machine Learning With Python
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Author : Andreas C. Müller
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-09-26

Introduction To Machine Learning With Python written by Andreas C. Müller and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-26 with Computers categories.


Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills



Introduction To Python For Humanists


Introduction To Python For Humanists
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Author : William Mattingly
language : en
Publisher: CRC Press
Release Date : 2023-07-26

Introduction To Python For Humanists written by William Mattingly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-26 with Business & Economics categories.


This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose. Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysis App development