The Writer's Guide to Training Your Dragon PDF Download

Author: Scott Baker
Publisher: Ashe Publishing
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 83

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Book Description
Want to dictate up to 5000 WORDS an hour? Want to do it with 99% ACCURACY from the day you start? NEW EDITION: UPDATED to cover the latest Dragon Professional Individual v15 for PC & v6 for Mac FREE video training included! As writers, we all know what an incredible tool dictation software can be. It enables us to write faster and avoid the dangers of RSI and a sedentary lifestyle. But many of us give up on dictating when we find we can't get the accuracy we need to be truly productive. This book changes all of that. With almost two decades of using Dragon software under his belt and a wealth of insider knowledge from within the dictation industry, Scott Baker will reveal how to supercharge your writing and achieve sky-high recognition accuracy from the moment you start using the software. You will learn: - Hidden tricks to use when installing Dragon NaturallySpeaking on a Windows PC or Dragon Dictate for Mac; - How to choose the right microphone and set it up perfectly for speech recognition; - The little-known techniques that will ensure around 99% accuracy from your first install – and how to make this even better over time; - Setting up fail-safe dictation profiles with multiple microphones and voice recorders, without impacting your accuracy; - How to train the software to adapt to both your voice AND writing style and avoid your accuracy declining; - Strategies for achieving your entire daily word count in just one or two hours; - Many more tips and tricks you won't find anywhere else. At the end of the book, you'll also find an exclusive list of resources and links to FREE video training to take your knowledge even further. It's time to write at the speed of speech – and transform your writing workflow forever! Subject keywords: Dragon Dictate Naturally Speaking for PC Mac, dictating your book or novel, dictation for writers authors beginners advanced, creative writing guides, self publishing

Author: Uday Kamath
Publisher: Springer
ISBN: 3030145964
Category : Computers
Languages : en
Pages : 640

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Book Description
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.

Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912

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Book Description

Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801

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Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Author: Monica Leonelle
Publisher: Spaulding House
ISBN: 1635660270
Category : Business & Economics
Languages : en
Pages : 103

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Book Description
Ready to get on board with dictation (finally)? Like many tools that have come before it, dictation is a new and exciting opportunity to write better, faster, and smarter. But many writers still believe it's not for them. Perhaps they've tried it in the past and it hasn't worked. Or perhaps this new technology is confusing, expensive, or frustrating and that's held them back from taking advantage of it. If you're ready to take the next step and learn a new skill set that will give you a huge advantage over what other authors are doing today, grab Dictate Your Book and start working through the challenges that are holding you back from reaping the benefits of dictation. It includes: - Why you need to get started with dictation, even if you tried it before and hated it! - All of Monica’s best tips for making dictation work for you, whether you writing fiction or nonfiction - Every piece of equipment Monica recommends, plus half a dozen ways to test dictation before you buy - How to reimagine your writing process to accommodate dictation and how to get that clean draft easily - Monica’s full setup for her innovative Walk ’n Talks which helped her hit 4,000+ words per hour For authors who are ready to take their productivity to the next level, this book will help you get started!

Author: Julie Flett
Publisher: Greystone Books Ltd
ISBN: 1771644745
Category : Juvenile Fiction
Languages : en
Pages : 56

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Book Description
BEST BOOK OF THE YEAR: PUBLISHERS WEEKLY, SCHOOL LIBRARY JOURNAL, KIRKUS, HORN BOOK, QUILL & QUIRE, GLOBE AND MAIL WINNER OF THE TD CANADIAN CHILDREN’S LITERATURE AWARD FINALIST FOR THE GOVERNOR GENERAL’S AWARD AN AMERICAN INDIAN YOUTH LITERATURE HONOR TITLE A BOSTON GLOBE—HORN BOOK HONOR BOOK When Katherena and her mother move to a small town, Katherena feels lonely and out of place. But when she meets an elderly woman artist who lives next door, named Agnes—her world starts to change. Katherena and Agnes share the same passions for arts and crafts, birds, and nature. But as the seasons change, can Katherna navigate the failing health of her new friend? Award-winning author and artist Julie Flett’s textured images of birds, flowers, art, and landscapes bring vibrancy and warmth to this powerful story, which highlights the fulfillment of intergenerational relationships, shared passions, and spending time outdoors with the ones we love. Includes a glossary and pronunciation guide to Cree words that appear in the text. “Cree-Métis author/illustrator Julie Flett's smooth and lyrical words and gorgeous... images truly capture the warmth and solidarity of the female protagonists in this tender intergenerational friendship story.”—The Horn Book “Cycling from spring to spring, [Julie Flett’s] subtle, sensitive story delicately traces filaments of growth and loss through intergenerational friendship, art making, and changing moons and seasons.” —Publishers Weekly (starred review)

Author: Alberto Artasanchez
Publisher: Packt Publishing Ltd
ISBN: 1839216077
Category : Computers
Languages : en
Pages : 619

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Book Description
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.

Author: A Purushotham Reddy
Publisher: A Purushotham Reddy
ISBN:
Category : Antiques & Collectibles
Languages : en
Pages : 2066

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Book Description
Database Management Using AI: A Comprehensive Guide is a professional yet accessible exploration of how artificial intelligence (AI) is reshaping the world of database management. Designed for database administrators, data scientists, and tech enthusiasts, this book walks readers through the transformative impact of AI on modern data systems. The guide begins with the fundamentals of database management, covering key concepts such as data models, SQL, and the principles of database design. From there, it delves into the powerful role AI plays in optimizing database performance, enhancing security, and automating complex tasks like data retrieval, query optimization, and schema design. The book doesn't stop at theory. It brings AI to life with practical case studies showing how AI-driven database systems are being used in industries such as e-commerce, healthcare, finance, and logistics. These real-world examples demonstrate AI's role in improving efficiency, reducing errors, and driving intelligent decision-making. Key topics covered include: Introduction to Database Systems: Fundamentals of database management, from relational databases to modern NoSQL systems. AI Integration: How AI enhances database performance, automates routine tasks, and strengthens security. Real-World Applications: Case studies from diverse sectors like healthcare, finance, and retail, showcasing the practical impact of AI in database management. Predictive Analytics and Data Mining: How AI tools leverage data to make accurate predictions and uncover trends. Future Trends: Explore cutting-edge innovations like autonomous databases and cloud-based AI solutions that are shaping the future of data management. With its clear explanations and actionable insights, Database Management Using AI equips readers with the knowledge to navigate the fast-evolving landscape of AI-powered databases, making it a must-have resource for those looking to stay ahead in the digital age.

Author: Homayoon Beigi
Publisher: Springer Science & Business Media
ISBN: 0387775927
Category : Technology & Engineering
Languages : en
Pages : 984

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Book Description
An emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks, call centres and other enterprise businesses for business process automation. "Fundamentals of Speaker Recognition" introduces Speaker Identification, Speaker Verification, Speaker (Audio Event) Classification, Speaker Detection, Speaker Tracking and more. The technical problems are rigorously defined, and a complete picture is made of the relevance of the discussed algorithms and their usage in building a comprehensive Speaker Recognition System. Designed as a textbook with examples and exercises at the end of each chapter, "Fundamentals of Speaker Recognition" is suitable for advanced-level students in computer science and engineering, concentrating on biometrics, speech recognition, pattern recognition, signal processing and, specifically, speaker recognition. It is also a valuable reference for developers of commercial technology and for speech scientists. Please click on the link under "Additional Information" to view supplemental information including the Table of Contents and Index.

Author: Dong Yu
Publisher: Springer
ISBN: 1447157796
Category : Technology & Engineering
Languages : en
Pages : 329

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Book Description
This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.