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Название: Advanced Image Processing with Python and OpenCV: Implementing High-Performance Computer Vision Solutions for Object Detection, Image Recognition, and Augmented Reality Applications
Автор: Greyson Chesterfield
Издательство: Donbri Publishers
Год: 2024
Страниц: 159
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Unlock the full potential of Python and OpenCV with Advanced Image Processing with Python and OpenCV. This comprehensive guide delves into high-performance computer vision techniques that power today's cutting-edge technologies, including object detection, image recognition, and augmented reality. Designed for both beginners and seasoned developers, this book provides step-by-step guidance through complex topics, from setting up your environment to advanced image processing techniques. Whether you're creating robust applications for healthcare, autonomous vehicles, or dynamic media, you’ll find the techniques and code examples to bring your projects to life. With clear explanations and hands-on exercises, you'll gain practical skills in image filtering, geometric transformations, feature extraction, deep learning-based segmentation, and much more. Equip yourself with the knowledge to solve real-world challenges and advance in the rapidly growing field of computer vision. Computer vision is a subfield of Artificial Intelligence (AI) that focuses on enabling machines to interpret and understand visual information from the world. It aims to replicate human vision capabilities, allowing computers to process and analyze images or video streams to derive meaningful information. The significance of computer vision is highlighted by its ability to automate tasks that require visual understanding. Python, a versatile and user-friendly programming language, has gained immense popularity in the field of computer vision due to its simplicity and readability. The combination of OpenCV and Python allows developers to implement complex image processing tasks with minimal code, making it an ideal choice for both beginners and experienced practitioners.

Название: Probability, Statistics and Maths for AI: A comprehensive guide to understanding probability, statistics, and mathematics for AI
Автор: Et Tu Code
Издательство: Independently published
Год: 2024
Страниц: 657
Язык: английский
Формат: epub
Размер: 29.5 MB

Master the fundamental concepts of probability, statistics, and math to excel in Artificial Intelligence (AI)! Probability, Statistics, and Maths for AI is designed to provide readers with a comprehensive guide to these fundamental concepts that underlie AI systems. The book is aimed at students, researchers, and professionals who want to gain a solid grasp of the mathematical foundations of AI. Whether you are new to AI or looking to deepen your understanding, this book will take you on a journey through the key concepts and techniques that are essential for building intelligent systems. Probability theory is a cornerstone of AI, as it enables machines to make predictions about uncertain events and outcomes. From Bayes' theorem to Markov chains, probability provides the mathematical framework for AI algorithms to reason about uncertainty. Statistics plays a crucial role in AI by enabling the development of robust and reliable machine learning models. Statistical techniques such as regression analysis, hypothesis testing, and confidence intervals are essential for evaluating the performance of AI systems. Mathematics is the glue that holds AI together. From linear algebra to calculus, mathematical concepts provide the building blocks for AI algorithms to reason about data, optimize processes, and make decisions. Throughout this book, we will explore these fundamental concepts in depth, providing examples, exercises, and real-world applications to illustrate their importance. We will also delve into the practical implications of these concepts for AI systems, highlighting how they are used in popular AI frameworks such as TensorFlow, PyTorch, and Keras. By the end of this book, readers will have gained a comprehensive understanding of probability, statistics, and mathematics that is essential for building intelligent AI systems. Whether you're a beginner or looking to deepen your understanding of AI, this book is the perfect resource.

Название: Random Number Generators on Computers
Автор: Naoya Nakazawa, Hiroshi Nakazawa
Издательство: Jenny Stanford Publishing
Год: 2025
Страниц: 121
Язык: английский
Формат: pdf (true), epub
Размер: 11.6 MB

This monograph proves that any finite random number sequence is represented by the multiplicative congruential (MC) way. It also shows that an MC random number generator (d, z) formed by the modulus d and the multiplier z should be selected by new regular simplex criteria to give random numbers an excellent disguise of independence. The new criteria prove further that excellent subgenerators (d1,z1) and (d2,z2) with coprime odd submoduli d1 and d2 form an excellent combined generator (d = d1d2,z) with high probability by Sunzi’s theorem of the 5th-6th centuries (China), contrasting the fact that such combinations could never be found with MC subgenerators selected in the 20th-century criteria. We restrict ourselves to problems of random numbers on computers. We are happy to see many simplifications. Numbers on computers are essentially integers in various sense. We thus need only integer sequences placed on discrete time points; the setting gives random numbers as the outcome of a huge dice thrown in computers at discrete times. Yet, we have still to discuss that the dice is fair and the throwing is not deceitful. We present here what we have found within this restricted circumstance. You will be surprised to see that Numbers, which existed from the beginning of this universe, seem to have prepared neat answers to the present computer problems.

Название: Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure
Автор: Dayne Sorvisto
Издательство: Microsoft Press/Pearson Education
Год: 2025
Страниц: 192
Язык: английский
Формат: epub
Размер: 12.5 MB

Prepare for Microsoft Exam DP-100 and demonstrate your real-world knowledge of managing data ingestion and preparation, model training and deployment, and Machine Learning solution monitoring with Python, Azure Machine Learning, and MLflow. Designed for professionals with Data Science experience, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Scientist Associate level. This book is written for IT professionals who intend to take the DP-100 exam as well as data engineers, data scientists, and other data professionals who want to learn to design and implement a Data Science solution in Azure. In addition to the exam material, the book is meant to enrich your knowledge of Azure Machine Learning by using it to implement Machine Learning operations in Azure and to design end-to-end Data Science solutions. Exam DP-100 focuses on knowledge needed to design and prepare a Machine Learning solution, manage an Azure Machine Learning workspace, explore data and train models, create models by using the Azure Machine Learning designer, prepare a model for deployment, manage models in Azure Machine Learning, deploy and retrain a model, and apply machine learning operations (MLOps) practices.

Название: The Joys of Hashing: Hash Table Programming with C, 2nd Edition
Автор: Thomas Mailund
Издательство: Apress
Год: 2024
Страниц: 225
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Build working implementations of hash tables, written in the C programming language. The new and revised Second Edition has been enhanced with simplified code and more comprehensive explanations, aimed at improving clarity and comprehension while exploiting the latest features in C programming. This book starts with simple first attempts devoid of collision resolution strategies. It then progresses through improvements and extensions illustrating different design ideas and approaches, followed by experiments to validate the choices. You will learn how hash tables, when implemented and used appropriately, are exceptionally efficient data structures for representing sets and lookup tables, providing low overhead, constant time, insertion, deletion, and lookup operations. This book is an introduction to the hash table data structure. When implemented and used appropriately, hash tables are exceptionally efficient data structures for representing sets and lookup tables. They provide constant time, low overhead, insertion, deletion, and lookup. This book assumes you are familiar with programming and the C programming language. The theoretical parts of the book also assume some familiarity with probability theory and algorithmic theory, but nothing beyond what you would learn in an introductory course. The Joys of Hashing walks you through the implementation of efficient hash tables and the pros and cons of different design choices when building tables. The source code used in the book is available on GitHub for your re-use and experiments.

Название: Rust Projects - Write a Redis Clone: Explore asynchronous programming with the actor model using Rust and Tokio
Автор: Leonardo Giordani
Издательство: Leanpub
Год: 2024-10-16 (Release 1.0.0)
Страниц: 147
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Explore the power of Rust with "Rust Projects: Write a Redis Clone". This hands-on guide takes you through building a Redis-inspired database from the ground up, introducing key programming concepts like TCP connections, the RESP protocol, and concurrency. Following the CodeCrafters challenge, this book gradually builds your skills, making complex topics accessible. Whether you're new to Rust or looking to deepen your understanding, this project-based journey offers practical, real-world insights into modern systems programming. "Rust Projects: Write a Redis Clone" is a hands-on guide for building a Redis-like database while mastering Rust. The book follows the CodeCrafters challenge of the same name. Readers will start by learning concepts like binding to TCP ports and setting up a server, progressively covering more complex tasks, such as handling multiple client connections and implementing key Redis commands. The book introduces the RESP protocol, covering how to parse and manage binary data and implement basic Redis commands like GET and SET. It also covers how to implement active and passive key expiry mechanisms. The book culminates with an overview of the actor model and a concurrency implementation that simplifies the management of shared resources. "Rust Projects: Write a Redis Clone" is more than a technical manual; it's a project-based journey through Rust. With plans to cover advanced features like replication and transactions, this book serves as a valuable resource for Rust enthusiasts eager to build real-world applications from scratch.

Название: Financial Data Analytics with Machine Learning, Optimization and Statistics
Автор: Sam Chen, Ka Chun Cheung, Phillip Yam
Издательство: Wiley
Год: 2025
Страниц: 816
Язык: английский
Формат: epub (true)
Размер: 98.4 MB

An essential introduction to data analytics and Machine Learning techniques in the business sector. In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data analysts delivers an expertly balanced combination of traditional financial statistics, effective Machine Learning (ML) tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs—especially of key results—and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves. The book begins with a brief introduction to basic sampling theory and the fundamentals of simulation techniques, followed by a comparison between R and Python. It then discusses statistical diagnosis for financial security data and introduces some common tools in financial forensics such as Benford's Law, Zipf's Law, and anomaly detection. Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, Data Science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.

Название: Mastering OpenTelemetry and Observability: Enhancing Application and Infrastructure Performance and Avoiding Outages
Автор: Steve Flanders
Издательство: Wiley
Год: 2025
Страниц: 368
Язык: английский
Формат: epub (true)
Размер: 14.8 MB

Discover the power of open source observability for your enterprise environment. In Mastering Observability and OpenTelemetry: Enhancing Application and Infrastructure Performance and Avoiding Outages, accomplished engineering leader and open source contributor Steve Flanders unlocks the secrets of enterprise application observability with a comprehensive guide to OpenTelemetry (OTel). Explore how OTel transforms observability, providing a robust toolkit for capturing and analyzing telemetry data across your environment. You will learn how OTel delivers unmatched flexibility, extensibility, and vendor neutrality, freeing you from vendor lock-in and enabling data sovereignty and portability. Beyond technical guidance, this book also addresses the human and organizational aspects of observability. This is because building a culture of observability within your team and organization is crucial for success. This book discusses strategies for fostering collaboration, continuous improvement, and proactive incident response, ensuring that observability becomes an integral part of your operational practices. Finally, this book explores emerging trends and innovations in observability, including the role of Artificial Intelligence (AI) and Machine Learning (ML) in predictive analytics, the evolution of observability standards, and the potential impact of new technologies on the industry. A containerized Python application will be primarily used, but differences between Python and other programming languages will also be explored. In addition, the examples in this chapter are optimized for Linux, but modifying them for operating systems such as Windows should be relatively easy. While some basic Python knowledge is helpful, the prescriptive steps that follow should work as long as the environment is properly configured with the following prerequisites: • curl; • Docker. Whether you are a novice or a seasoned professional, Mastering Observability and OpenTelemetry is your roadmap to troubleshooting availability and performance problems by learning to detect anomalies, interpret data, and proactively optimize performance in your enterprise environment. Embark on your journey to observability mastery today!

Название: Pragmatic Type-Level Design
Автор: Alexander Granin
Издательство: Leanpub
Год: 2024 (v.0.9.1)
Страниц: 331
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Practical introduction into type-level programming: design principles, design patterns, methodologies, approaches. An approachable, well-written, practice-oriented, academism-free guide into programming with types. How to build useful real-world type-level programs with low complexity and low risks. Pragmatic Type-Level Design is a book about programming in types, about the discipline of Software Design, lifted onto the level of types, and type-level approaches useful in real practice. I aim to provide a well-written and well-structured source of knowledge about type-level design. I’m not only talking about type-level features but also providing a reasoning framework for making the narrative complete and comprehensive. The central philosophy of this book - pragmatism - is used to build a practice-first methodology on how to approach types and not drown in the related complexity. The type-level design is difficult on its own, type-level features in various languages are difficult as well, and there is no need to raise the learning bar even more. Type-level programming has been around for a while, with many languages boasting rich type systems. It’s a domain beloved by many, especially in Haskell, where types are one of the language’s most compelling features. Haskell developers often gravitate toward the mathematical foundations of types, like Category Theory and Type Theory. Good old Haskell 2010 introduces a lot of type-level features. Type definitions, type classes, type variables, constraints, kinds, phantom types, and algebraic data types. With dozens of modern GHC extensions, it becomes orders of magnitude more powerful. Type-level literals, type families, multi-parameter type classes, generalized algebraic data types, different options for type-level polymorphism, et cetera, et cetera – it’s too long to enumerate all these tools, what to say about the explosion of all possible ways to combine them. The book will be useful for developers who want to start doing real things on the type level.

Название: MATLAB Programming: Advanced Data Analysis, Visualisation, and Large-Scale Applications for Research and Development
Автор: Theophilus Edet
Издательство: CompreQuest Books
Год: 2024
Страниц: 734
Язык: английский
Формат: epub
Размер: 10.1 MB

Unleash Your Potential with MATLAB: Advanced Tools for Innovation. MATLAB Programming: Advanced Data Analysis, Visualization, and Large-Scale Applications for Research and Development is your ultimate guide to mastering MATLAB. This powerful programming environment is designed for engineers, scientists, and researchers, enabling advanced data analysis, stunning visualizations, and large-scale applications with ease. If you’re ready to elevate your programming skills, this book is for you. Discover MATLAB’s 11 Programming Models for Versatile Applications: MATLAB offers strong core support for 11 essential programming models that empower you to tackle diverse challenges effectively in areas of fundamental, modular, data-focused, concurrent, and logic/rule-based Paradigms by exploring Imperative Programming, Procedural Programming, Structured Programming, Component-Based Programming, Object-Oriented Programming (OOP), Array Programming, Data-Driven Programming, Concurrent Programming, Event-Driven Programming, Parallel Programming, and Functional Programming. Each model enhances MATLAB’s capabilities, allowing you to create high-performance solutions tailored to your needs. MATLAB is more than just a tool for quick calculations and plotting graphs—it is a powerful programming environment that supports various programming models. This flexibility allows MATLAB users to choose the most appropriate paradigm for their specific task, enabling them to build efficient, scalable, and maintainable solutions for a wide range of applications. This book explores MATLAB’s core strengths across eleven distinct programming paradigms, illustrating how MATLAB can adapt to each approach depending on the demands of the problem at hand. MATLAB Programming: Advanced Data Analysis, Visualization, and Large-Scale Applications for Research and Development is an essential resource for anyone looking to harness the full potential of MATLAB. Whether you are a beginner or an experienced programmer, this book will guide you through the complexities of MATLAB, empowering you to create advanced data analyses, stunning visualizations, and robust applications.