Название: Automatic Speech Recognition and Translation for Low Resource Languages Автор: L. Ashok Kumar, D. Karthika Renuka, Bharathi Raja Chakravarthi 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.
Название: Cognitive Analytics and Reinforcement Learning: Theories, Techniques and Applications Автор: Elakkiya R., Subramaniyaswamy V. Издательство: Wiley-Scrivener Год: 2024 Страниц: 384 Язык: английский Формат: epub Размер: 10.1 MB
The combination of cognitive analytics and Reinforcement Learning is a transformational force in the field of modern technological breakthroughs, reshaping the decision-making, problem-solving, and innovation landscape; this book offers an examination of the profound overlap between these two fields and illuminates its significant consequences for business, academia, and research. Cognitive analytics and Reinforcement Learning are pivotal branches of Artificial Intelligence. They have garnered increased attention in the research field and industry domain on how humans perceive, interpret, and respond to information. Cognitive science allows us to understand data, mimic human cognitive processes, and make informed decisions to identify patterns and adapt to dynamic situations. The process enhances the capabilities of various applications. Readers will uncover the latest advancements in AI and Machine Learning, gaining valuable insights into how these technologies are revolutionizing various industries, including transforming healthcare by enabling smarter diagnosis and treatment decisions, enhancing the efficiency of smart cities through dynamic decision control, optimizing debt collection strategies, predicting optimal moves in complex scenarios like chess, and much more. The book caters to a diverse audience that spans academic researchers, AI practitioners, data scientists, industry leaders, tech enthusiasts, and educators who associate with Artificial Intelligence, data analytics, and cognitive sciences.
Название: Data Science Fundamentals with R, Python, and Open Data Автор: Marco Cremonini Издательство: Wiley Год: 2024 Страниц: 461 Язык: английский Формат: epub Размер: 10.1 MB
Introduction to essential concepts and techniques of the fundamentals of R and Python needed to start Data Science projects. Organized with a strong focus on open data, Data Science Fundamentals with R, Python, and Open Data discusses concepts, techniques, tools, and first steps to carry out Data Science projects, with a focus on Python and RStudio, reflecting a clear industry trend emerging towards the integration of the two. The text examines intricacies and inconsistencies often found in real data, explaining how to recognize them and guiding readers through possible solutions, and enables readers to handle real data confidently and apply transformations to reorganize, indexing, aggregate, and elaborate. This book is full of reader interactivity, with a companion website hosting supplementary material including datasets used in the examples and complete running code (R scripts and Jupyter notebooks) of all examples. Exam-style questions are implemented and multiple choice questions to support the readers’ active learning. Each chapter presents one or more case studies. Data Science Fundamentals with R, Python, and Open Data is a highly accessible learning resource for students from heterogeneous disciplines where Data Science and quantitative, computational methods are gaining popularity, along with hard sciences not closely related to Computer Science, and medical fields using stochastic and quantitative models.
Learn how to find the unusual, interesting, extreme, or inaccurate parts of your data. Outliers can be the most informative parts of your data, revealing hidden insights, novel patterns, and potential problems. For a business, this can mean finding new products, expanding markets, and flagging fraud or other suspicious activity. Outlier Detection in Python introduces the tools and techniques you’ll need to uncover the parts of a dataset that don’t look like the rest, even when they’re the more hidden or intertwined among the expected bits. Outlier Detection in Python is a comprehensive guide to the statistical methods, Machine Learning, and Deep Learning approaches you can use to detect outliers in different types of data. Throughout the book, you’ll find real-world examples taken from author Brett Kennedy’s extensive experience developing outlier detection tools for financial auditors and social media analysis. Plus, the book’s emphasis on interpretability ensures you can identify why your outliers are unusual and make informed decisions from your detection results. Each key concept and technique is illustrated with clear Python examples. All you’ll need to get started is a basic understanding of statistics and the Python data ecosystem. For Python programmers familiar with tools like pandas and NumPy, and the basics of statistics.
Название: 100 C++ Mistakes and How to Avoid Them (MEAP v2) Автор: Rich Yonts Издательство: Manning Publications Год: 2024 Страниц: 220 Язык: английский Формат: pdf, azw3, epub, mobi Размер: 10.1 MB
Learn how to handle errors, inefficiencies, and outdated paradigms by exploring the most common mistakes you’ll find in production C++ code. C++ is a complex and powerful language. With an estimated ten billion lines of C++ code running in production, it’s not hard to find bugs, inefficiencies, and other coding mistakes that slow and snarl even the most mission critical applications. 100 C++ Mistakes and How To Avoid Them reveals the problems you’ll inevitably encounter as you write new C++ code and diagnose legacy applications, along with practical techniques you need to resolve them. 100 C++ Mistakes and How To Avoid Them identifies the problems you’ll find in legacy C++ codebases as well as in your own new programs. Author Rich Yonts provides a concrete example of each mistake and a step-by-step walkthrough of the correct code. You’ll learn to consider each mistake from the standpoint of correctness, readability, effectiveness, and performance, and adopt modern programming techniques that can replace older, outdated approaches. The book focuses on newer developers who inherit existing C++ projects. Understanding why specific mistakes exist helps you know how to detect and avoid writing similar issues. The mistakes start with class design and end with a few modern C++ techniques. Learning these new features should encourage you to improve your inherited code and leave it in a much better state for the next developer. Both beginning and experienced C++ programmers will benefit from these practical tips and advice.
Название: The Python Bible for Beginners: The Ultimate Roadmap to Learn Python, Develop Practical Skills, and Kickstart Your Programming Career in Just 7 Days Автор: Ralston Maki Издательство: Independently published Год: 2024 Страниц: 238 Язык: английский Формат: pdf Размер: 26.8 MB
Reach the end of the book to redeem 3 exclusive ebooks! Unleash your coding potential with the ultimate Python Bible for Beginners! Are you ready to skyrocket your programming career in just 7 days? Do you dream of mastering Python and developing practical, in-demand skills? Have you been searching for a comprehensive guide that takes you from zero to hero in record time? If so, keep reading! This groundbreaking book is your fast track to Python mastery. Packed with clear explanations, hands-on projects, and expert insights, it's the only resource you need to go from complete beginner to confident coder in just one week. Whether you're looking to jumpstart your programming career, automate tasks, or bring your ideas to life, this bible has everything you need to succeed. Whether you're a complete novice, a career changer, or a programmer looking to add Python to your toolkit, this bible is your key to unlocking the full potential of this versatile language. With its laser focus on practical skills and job readiness, it's the ultimate resource for anyone serious about launching a successful programming career.
Название: Fluent Bit with Kubernetes (MEAP v5) Автор: Phil Wilkins Издательство: Manning Publications Год: 2024 Страниц: 341 Язык: английский Формат: pdf, epub Размер: 16.8 MB
Build cloud native observability pipelines with minimal footprints and high-performance throughput—all with Fluent Bit, Kubernetes, and your favorite visualization and analytics tools. Fluent Bit with Kubernetes draws on both the input and support of key committers and founders of Fluent Bit, and author Phil Wilkin’s years of experience in DevOps. Inside, you’ll see how you can integrate Fluent Bit with Prometheus, OpenTelemetry, FluentD deployments, and more. Learn how Fluent Bit can not only meet all the demands of cloud-native use cases, but also more traditional deployments as well. Inside Fluent Bit with Kubernetes you’ll learn how to establish and optimize observability systems for Kubernetes, and more. From fundamental configuration to advanced integrations, this book lays out Fluent Bit’s full capabilities for log, metric, and trace routing and processing. You’ll start with pre-made configurations for universal use cases, steadily working your way up to see how Fluent Bit works with modern innovations like OpenTelemetry and real-time analytical processing of events. You’ll learn how to customize filtering and processing using Lua scripts and plugins, and meet the demands of highly scalable environments with a minimal footprint. By the end, you’ll be ready to build tailored observability pipelines efficiently using Fluent Bit. For developers, DevOps engineers, and SREs working with Kubernetes observability.
Название: Visualizing Quantum Mechanics with Python Автор: Stephen Spicklemire Издательство: CRC Press Год: 2024 Язык: английский Формат: pdf (true) Размер: 10.1 MB
Quantum Mechanics can be an abstract and complex subject. Students often complain of confusion, struggle, and frustration as they try to master the topic. The goal of this book is to reduce the complexity and clarify the abstractions with concrete visual examples driven by simple Python programs. It is assumed that the reader is concurrently taking a course in quantum mechanics, or self-studying quantum mechanics, but is looking for supplementary material to help with understanding and visualizing how quantum mechanics works. The focus of this book is writing Python programs to visualize the underlying behavior of the mathematical theory. The background needed to understand quantum mechanics is differential equations, linear algebra and modern physics. We need a strong foundation in differential equations and linear algebra because the behavior of quantum systems is governed by equations that are written in terms of these concepts. Modern physics includes concepts such as special relativity and quantum phenomena like the photoelectric effect and energy quantization that the theory of quantum mechanics seeks to explain. This book is also not an introduction to the Python programming language, or to NumPy, or even to VPython. However its programming examples start simply and grow more complex as the chapters progress, so deep expertise in any of these is not a pre-requisite.
Название: Mastering Large Language Models: Advanced techniques, applications, cutting-edge methods, and top LLMs Автор: Sanket Subhash Khandare 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).
Supercharge your applications with the ultimate guide to asynchronous and multithreaded programming in C#! C# Concurrency: Asynchronous and Multithreaded Programming teaches you to harness the power of multithreading and async/await to get maximum speed from your code. Nir Dobovizki, a seasoned C# veteran with over 30 years of high-performance programming experience, is here to share his deep knowledge and expert techniques with you. Say goodbye to frustrating pitfalls and impossible-to-find bugs that slow down your applications. Nir's careful approach will teach you how to navigate these challenges with ease, allowing you to achieve lightning-fast performance like never before! Concurrency is a developers’ secret weapon for maximizing an application's performance. Using asynchronous and multithreaded programming techniques, you can seamlessly execute multiple tasks simultaneously, without sacrificing speed or quality.
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Название: C# Concurrency: Asynchronous and multithreaded programming (MEAP v10)