Название: Automatic Speech Recognition and Translation for Low Resource Languages
Автор: L. Аshоk Кumаr, D. Каrthikа Rеnukа, Вhаrаthi Rаjа Сhаkrаvаrthi
Издательство: Wiley-Scrivener
Год: 2024
Страниц: 646
Язык: английский
Формат: epub
Размер: 42.5 MB

This book is a comprehensive exploration into the cutting-edge research, methodologies, and advancements in addressing the unique challenges associated with ASR and translation for low-resource languages. Automatic Speech Recognition and Translation for Low Resource Languages contains groundbreaking research from experts and researchers sharing innovative solutions that address language challenges in low-resource environments. The book begins by delving into the fundamental concepts of ASR and translation, providing readers with a solid foundation for understanding the subsequent chapters. It then explores the intricacies of low-resource languages, analyzing the factors that contribute to their challenges and the significance of developing tailored solutions to overcome them. The chapters encompass a wide range of topics, ranging from both the theoretical and practical aspects of ASR and translation for low-resource languages. The book discusses data augmentation techniques, transfer learning, and multilingual training approaches that leverage the power of existing linguistic resources to improve accuracy and performance. Additionally, it investigates the possibilities offered by unsupervised and semi-supervised learning, as well as the benefits of active learning and crowdsourcing in enriching the training data. The book targets researchers and professionals in the fields of natural language processing, computational linguistics, and speech technology.[left][/left]

Название: Mastering Large Language Models: Advanced techniques, applications, cutting-edge methods, and top LLMs
Автор: Sаnkеt Subhаsh Кhаndаrе
Издательство: BPB Publications
Год: 2024
Страниц: 903
Язык: английский
Формат: pdf, epub
Размер: 13.2 MB

Do not just talk AI, build it: Your guide to LLM application development. Transform your business landscape with the formidable prowess of large language models (LLMs). The book provides you with practical insights, guiding you through conceiving, designing, and implementing impactful LLM-driven applications. This book explores NLP fundamentals like applications, evolution, components and language models. It teaches data pre-processing, neural networks, and specific architectures like RNNs, CNNs, and transformers. It tackles training challenges, advanced techniques such as GANs, meta-learning, and introduces top LLM models like GPT-3 and BERT. It also covers prompt engineering. Finally, it showcases LLM applications and emphasizes responsible development and deployment. With this book as your compass, you will navigate the ever-evolving landscape of LLM technology, staying ahead of the curve with the latest advancements and industry best practices. This book is tailored for those aiming to master large language models, including seasoned researchers, data scientists, developers, and practitioners in natural language processing (NLP).

Название: GPT-4. Руководство по использованию API Open AI
Автор: Aймeн Эль Aмpи
Издательство: ДМК Пресс
Год: 2024
Страниц: 276
Язык: русский
Формат: pdf
Размер: 13.4 MB

В книге рассказывается о том, как использовать генеративные текстовые модели поколений GPT-3.5 и GPT-4 для создания приложений различного назначения, в числе которых интерактивный психотерапевт, интеллектуальный голосовой помощник, система рекомендации товаров, генератор заметок в соцсетях, система распознавания речи и многие другие. Вы научитесь использовать векторные базы данных, узнаете, как управлять уровнем креативности моделей GPT, применять современные методы генерирования высококачественного текста, и даже организуете диалог между двумя чат-ботами. Примеры и практические упражнения помогут закрепить пройденный материал. Издание предназначено для тех, кто владеет основами языка программирования Python и собирается использовать GPT в реальных сценариях для решения прикладных задач. Если вы владеете основами языка программирования Python и готовы изучить еще несколько инструментов, таких как объекты Dataframe библиотеки Pandas и некоторые методы NLP, значит, у вас есть под рукой все необходимое для создания интеллектуальных систем с использованием инструментов OpenAI. Не беспокойтесь, вам не нужно быть специалистом по данным, инженером по машинному обучению или экспертом по искусственному интеллекту, чтобы понять концепции, методы и учебные примеры, представленные в этой книге. Все объяснения предельно просты для понимания, в них используется базовый код Python, примеры и практические упражнения. Эта книга сфокусирована на практической части обучения и призвана помочь читателю создавать реальные приложения.

Название: Accountable and Explainable Methods for Complex Reasoning over Text
Автор: Рерa Аtаnаsоvа
Издательство: Springer
Год: 2024
Страниц: 208
Язык: английский
Формат: pdf (true)
Размер: 26.7 MB

This thesis presents research that expands the collective knowledge in the areas of accountability and transparency of Machine Learning (ML) models developed for complex reasoning tasks over text. In particular, the presented results facilitate the analysis of the reasons behind the outputs of ML models and assist in detecting and correcting for potential harms. It presents two new methods for accountable ML models; advances the state of the art with methods generating textual explanations that are further improved to be fluent, easy to read, and to contain logically connected multi-chain arguments; and makes substantial contributions in the area of diagnostics for explainability approaches. All results are empirically tested on complex reasoning tasks over text, including fact checking, question answering, and natural language inference. A major concern with Machine Learning (ML) models is their opacity. They are deployed in an increasing number of applications where they often operate as black boxes that do not provide explanations for their predictions. Among others, the potential harms associated with a lack of understanding of the models’ rationales include privacy violations, adversarial manipulations, and unfair discrimination. In Computer Science, the decision-making process of ML models has been studied by developing accountability and transparency methods. Accountability methods, such as adversarial attacks and diagnostic datasets, expose vulnerabilities in ML models that could lead to malicious manipulations or systematic faults in their predictions.

Название: Culture Coding: Harness technology, Artificial Intelligence and behavioural science to empower your business culture and performance
Автор: Сhris Dаviеs
Издательство: Rethink Press
Год: September 15, 2023
Страниц: 202
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

In the midst of the Fourth Industrial Revolution, your organisation must harness technology, Artificial Intelligence and digital tools to stay ahead in your field. Fail to do so, and you won’t survive. Culture Coding provides five keys to building a digitally focused, constructive culture that engages staff, delivers for clients and ensures success. It shows you how to take advantage of technology, AI and behavioural science to enable a culture for digital and sustainable business growth, whether you lead a startup, an SME or a multinational enterprise. Generative AI is a subset of Machine Learning that involves using algorithms to generate new content, such as images, music, text, or even videos. Unlike traditional Machine Learning algorithms that are trained on large datasets and used to make predictions based on that data, generative AI models are trained to create entirely new content based on the patterns and structures present in the data. Generative AI can be divided into two main categories: discriminative models and generative models. Discriminative models are used to classify or recognize data, while generative models are used to create new data.

Название: Computational Imaging and Analytics in Biomedical Engineering: Algorithms and Applications
Автор: Т.R. Gаnеsh Ваbu, U. Sаrаvаnаkumаr, Ваlасhаndrа Раttаnаik
Издательство: Apple Academic Press/CRC Press
Серия: AAP Series on Digital Signal Processing, Computer Vision and Image Processing
Год: 2024
Страниц: 356
Язык: английский
Формат: pdf (true)
Размер: 27.9 MB

This new book focuses on mathematical and numerical methods for medical images and data. The book presents the various mathematical modeling techniques, numerical analysis, computing and computational techniques, and applications of machine learning for medical images and medical informatics. It also focuses on programming concepts using MATLAB and Python for medical image and signal analytics. The volume demonstrates the use of computational techniques and tools such as Machine Learning, deep neural networks, Artificial Intelligence (AI) and human-computer interaction ,fusion methods for CT and pet images, etc., for diagnosis of brain disorders, cervical cancer, lung disease, melanoma, atrial fibrillation and other circulatory issues, dental images, diabetes, and other medical issues. For further simplification and optimization, emerging techniques such as neural networks, Machine Learning, Deep Learning (DL), and Artificial Intelligence (AI) are adapted for feature extraction of medical images, medical image segmen­tation, and image-based bio-models. Image categorization, object identifica­tion, pattern recognition, and reasoning are just a few of the principles that are examined in medical imaging. By extracting meaningful patterns for a specific condition, they are employed in medical imaging to improve accu­racy. They also aid in the process of deciding on a course of action. Using Machine Learning to improve medical imaging is a trend that will continue in the future.

Название: AI for Absolute Beginners: A Clear Guide to Tomorrow
Автор: Оlivеr Тhеоbаld
Издательство: Scatterplot Press
Серия: AI, Data Science, Python & Statistics for Beginners
Год: 2023
Страниц: 209
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

Curious about AI but feeling lost at the same time? Well, look no further! AI for Absolute Beginners is your guide to demystifying complex AI concepts and providing you with a solid foundation to step into and stay ahead in the new AI era. In this accessible and comprehensive book, we start from scratch, assuming no prior knowledge. Each chapter is carefully crafted to guide you through the fundamental concepts and practical applications of AI, including Machine Learning, generative AI, and Deep Learning. With clear and plain English explanations, you'll be surprised at how quickly you can start thinking and speaking fluently in the words and mindset of an AI expert! From self-driving cars to large language models, the ability of Deep Learning to learn from raw data and process large datasets has dramatically broadened the use cases for Artificial Intelligence (AI). However, like all technologies, Deep Learning has its own unique limitations and challenges that we will examine in this chapter. Before we dive in, it’s important to explain the connection between Deep Learning and Machine Learning. Machine Learning, as discussed, involves algorithms and models that improve with experience and exposure to data. As a subfield of Machine Learning, Deep Learning takes the foundational principles of Machine Learning and applies its own techniques to even larger and more complex datasets. This involves the use of artificial neural networks with deep and multiple layers stacked together to form a model.

Название: Linguistic Resources for Natural Language Processing: On the Necessity of Using Linguistic Methods to Develop NLP Software
Автор: Мах Silbеrztеin
Издательство: Springer
Год: 2024
Страниц: 230
Язык: английский
Формат: pdf (true), epub
Размер: 51.0 MB

Empirical ― data-driven, neural network-based, probabilistic, and statistical ― methods seem to be the modern trend. Recently, OpenAI’s ChatGPT, Google’s Bard and Microsoft’s Sydney chatbots have been garnering a lot of attention for their detailed answers across many knowledge domains. In consequence, most AI researchers are no longer interested in trying to understand what common intelligence is or how intelligent agents construct scenarios to solve various problems. Instead, they now develop systems that extract solutions from massive databases used as cheat sheets. In the same manner, Natural Language Processing (NLP) software that uses training corpora associated with empirical methods are trendy, as most researchers in NLP today use large training corpora, always to the detriment of the development of formalized dictionaries and grammars. Not questioning the intrinsic value of many software applications based on empirical methods, this volume aims at rehabilitating the linguistic approach to NLP. In an introduction, the editor uncovers several limitations and flaws of using training corpora to develop NLP applications, even the simplest ones, such as automatic taggers.

Название: PyTorch for Natural Language Processing Mastery: Build powerful dialogue models with Python
Автор: Jаmеs Russеl
Издательство: Independently published
Год: 2024
Страниц: 100
Язык: английский
Формат: pdf
Размер: 12.7 MB

Dialogue systems are revolutionizing human-computer interaction, enabling us to interact with machines in a natural and engaging way. But what about open-domain systems? These are the future, capable of extended conversations on any topic, just like you would with a friend. This book empowers you to conquer the world of Natural Language Processing (NLP) with the powerful PyTorch framework. Unleash the ability to build sophisticated dialogue systems, chatbots, and other interactive language applications using Python! For developer eager to harness the power of NLP and PyTorch for building innovative language applications, researcher seeking to delve deeper into the world of open-domain dialogue systems and explore new possibilities, student passionate about NLP and ready to solidify your understanding with practical application, anyone fascinated by the future of AI and human-computer interaction, eager to unlock the potential of dialogue systems.

Название: Data Analytics for Discourse Analysis with Python: The Case of Therapy Talk
Автор: Dеnnis Тау
Издательство: Routledge
Год: 2024
Страниц: 190
Язык: английский
Формат: pdf (true)
Размер: 16.5 MB

This concise volume, using examples of psychotherapy talk, showcases the potential applications of data analytics for advancing discourse research and other related disciplines. The book provides a brief primer on data analytics, defined as the science of analyzing raw data to reveal new insights and support decision making. Currently underutilized in discourse research, Tay draws on the case of psychotherapy talk, in which clients’ concerns are worked through via verbal interaction with therapists, to demonstrate how data analytics can address both practical and theoretical concerns. The Python code used to implement examples in the conceptual walkthroughs and case studies will be presented as they are discussed, for readers to try them out as they go along. The various code snippets throughout will be presented again at the end of each chapter to provide a bird’s-eye view of the logical flow of the techniques and their components. All code and data files are also available upon request and stored on my GitHub site. The numerical representation of different aspects of texts to facilitate subsequent quantitative analysis is a basic task in fields like corpus linguistics and natural language processing (NLP).