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Natural language processing (Computer science)

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Get up and running with the fundamentals of Amazon Alexa and build exciting IoT projects About This Book Gain hands-on experience of working with Amazon Echo and Alexa Build exciting IoT projects using Amazon Echo Learn about voice-enabled smart devices Who This Book Is For Alexa Skills Projects is for individuals who want to have a deep understanding of the underlying technology that drives Amazon Echo and Alexa, and how it can be integrated with the Internet of Things to develop hands-on projects. What You Will Learn Understand how Amazon Echo is already being used in various domains Discover how an Alexa Skill is architected Get a clear understanding of how some of the most popular Alexa Skills work Design Alexa Skills for specific purposes and interact with Amazon Echo to execute them Gain experience of programming for Amazon Echo Explore future applications of Amazon Echo and other voice-activated devices In Detail Amazon Echo is a smart speaker developed by Amazon, which connects to Amazon's Alexa Voice Service and is entirely controlled by voice commands. Amazon Echo is currently being used for a variety of purposes such as home automation, asking generic queries, and even ordering a cab or pizza. Alexa Skills Projects starts with a basic introduction to Amazon Alexa and Echo. You will then deep dive into Alexa Programming concepts such as Intents, Slots, Lambdas and maintaining your skill's state using DynamoDB. You will get a clear understanding of how some of the most popular Alexa Skills work, and gain experience of working with real-world Amazon Echo applications. In the concluding chapters, you will explore the future of voice-enabled applications and their coverage with respect to the Internet of Things. By the end of the book, you will have learned to design Alexa Skills for specific purposes and interact with Amazon Echo to execute these skills. Style and approach A practical guide filled with real world examples that will help you understand the process of creating Alexa Skills from scratch and it's real world applications. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

Natural language processing (Computer science)

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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. About This Book 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 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! 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 In Detail 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...

Natural language processing (Computer science) --- Computational linguistics.

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Natural language processing (Computer science) --- Speech processing systems

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Explore various approaches to organize and extract useful text from unstructured data using Java Key Features Use deep learning and NLP techniques in Java to discover hidden insights in text Work with popular Java libraries such as CoreNLP, OpenNLP, and Mallet Explore machine translation, identifying parts of speech, and topic modeling Book Description Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes. You'll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you'll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You'll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You'll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more. By the end of this book, you'll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications. What you will learn Understand basic NLP tasks and how they relate to one another Discover and use the available tokenization engines Apply search techniques to find people, as well as things, within a document Construct solutions to identify parts of speech within sentences Use parsers to extract relationships between elements of a document Identify topics in a set of documents Explore topic modeling from a document Who this book is for Natural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.

Natural language processing (Computer science) --- Java (Computer program language)