Название: Moral Codes: Designing Alternatives to AI
Автор: Alan F. Blackwell
Издательство: The MIT Press
Год: 2024
Страниц: 239
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Why the world needs less AI and better programming languages. Decades ago, we believed that robots and computers would take over all the boring jobs and drudgery, leaving humans to a life of leisure. This hasn't happened. Instead, humans are still doing boring jobs, and even worse, AI researchers have built technology that is creative, self-aware, and emotional—doing the tasks humans were supposed to enjoy. How did we get here? In Moral Codes, Alan Blackwell argues that there is a fundamental flaw in the research agenda of AI. What humanity needs, Blackwell argues, is better ways to tell computers what we want them to do, with new and better programming languages: More Open Representations, Access to Learning, and Control Over Digital Expression, in other words, MORAL CODE. Blackwell draws on his deep experiences as a programming language designer—which he has been doing since 1983—to unpack fundamental principles of interaction design and explain their technical relationship to ideas of creativity and fairness. Taking aim at software that constrains our conversations with strict word counts or infantilizes human interaction with likes and emojis, Blackwell shows how to design software that is better—not more efficient or more profitable, but better for society and better for all people. Covering recent research and the latest smart tools, Blackwell offers rich design principles for a better kind of software—and a better kind of world. In an introductory class in programming, students learn to code. They will be taught the syntax and keywords of some programming language notation, perhaps Python or Java, and will learn how to translate an algorithm into the conventional idioms of that particular programming language. Introductions to Machine Learning are not yet quite as familiar or popular as learn-­to-­code initiatives, but they are equally accessible to children—­I have a friend who teaches Machine Learning methods to eight-­year-­olds in an after-­school club.

Название: Graph Based Multimedia Analysis
Автор: Ananda S. Chowdhury, Abhimanyu Sahu
Издательство: Morgan Kaufmann/Elsevier
Год: 2024
Страниц: 370
Язык: английский
Формат: epub
Размер: 72.1 MB

Graph Based Multimedia Analysis applies concepts from graph theory to the problems of analyzing overabundant video data. Video data can be quite diverse: exocentric (captured by a standard camera) or egocentric (captured by a wearable device like Google Glass); of various durations (ranging from a few seconds to several hours); and could be from a single source or multiple sources. Efficient extraction of important information from such a large class of diverse video data can be overwhelming. The book, with its rich repertoire of theoretically elegant solutions, from graph theory in conjunction with deep learning, constrained optimization, and game theory, empowers the audience to achieve tasks like obtaining concise yet useful summaries and precisely recognizing single as well as multiple actions in a computationally efficient manner. The book provides a unique treatise on topics like egocentric video analysis and scalable video processing. This book provides a comprehensive and methodical approach to these challenges, underpinned by the rigorous and elegant framework of graph theory. It deftly bridges the gap between the somewhat disparate domains of video processing and graph theory, demonstrating how graph-based methodologies can effectively address critical problems in video summarization, cosummarization, and action recognition. The salient feature of this work is its extensive utilization of graph theoretical concepts. The book covers an impressive array of graph-based methods, including Delaunay graphs, Optimal Path-Forests, Bipartite Graph Matching, Graph Centrality measures, Graph Connectedness, Spectral Measures of Graph Similarity, Minimum Spanning Tree, and Random Walks. The integration of game-theoretic models, constrained optimization techniques, and advanced Deep Learning methods such as Convolutional Neural Networks and Transfer Learning, further enriches the suite of methods presented.

Название: Python Programming: Handbook For IoT Development: A Complete Beginners Guide To Learning Essential Skills To Build Connected Devices, Collect Data And Create Innovative Applications
Автор: Hazel Mackay
Издательство: Independently published
Серия: The Python Power Toolkit
Год: 2024
Страниц: 172
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Unleash the Power of Python for Your Next IoT Project: Python Programming Handbook for IoT Development. Transform your ideas into connected realities with this beginner-friendly guide! The Internet of Things (IoT) is exploding, and Python is the key that unlocks its potential. This handbook is your comprehensive roadmap to mastering Python for building smart, interconnected devices. No prior coding experience necessary! Python, with its simplicity, flexibility, and extensive libraries, has emerged as a language of choice for IoT development. Its versatility and ease of use make it an ideal choice for building robust, efficient, and scalable IoT applications, from smart home devices and industrial automation to wearable technology and environmental monitoring. This handbook is designed to take you on a journey from the basics of Python programming to the cutting-edge techniques and tools used in IoT development. Whether you're a seasoned developer looking to expand your skillset or a beginner eager to dive into the world of IoT, this book provides a clear, concise, and hands-on approach to learning Python programming for IoT development. By the end of this journey, you'll be a confident Python programmer, ready to embark on your own exciting IoT endeavors.

Название: Introduction to Python Network Automation Volume I - Laying the Groundwork, 2nd Edition
Автор: Brendan Choi
Издательство: Apress
Год: 2024
Страниц: 831
Язык: английский
Формат: pdf (true), epub (true)
Размер: 37.1 MB

Welcome to Introduction to Python Network Automation Volume I: Laying the Groundwork. In this first part of our comprehensive guide, you'll embark on a transformative journey into the world of network automation. Whether you're new to the IT field or seeking to strengthen your existing skills, this book serves as your roadmap to mastering the foundational skills essential for success in network automation. You'll begin your exploration by delving into the fundamentals of Python network automation, laying a solid foundation for your learning journey. Equipped with essential Python skills, you'll leverage them for network administration tasks, particularly on the Windows platform. Reinforce your understanding through targeted exercises designed to enhance your proficiency and navigate the complexities of VMware Workstation as you master virtualization techniques crucial for setting up your network automation environment. You’ll then venture into Linux fundamentals, learning to set up and configure server environments tailored for network automation tasks while gaining a deep understanding of file systems and TCP/IP services in Linux. Explore the power of regular expressions as you streamline network automation tasks with precision and efficiency. For IT engineers and developers, network managers and students, who would like to learn network automation using Python.

Название: Программирование на Python с помощью GitHub Copilot и ChatGPT
Автор: Портер Л., Зингаро Д.
Издательство: питер
Год: 2024
Формат: PDF
Страниц: 340
Размер: 42 Mb
Язык: Русский

В наши дни люди пишут компьютерные программы совсем не так, как раньше. Используя GitHub Copilot, можно простым языком описать, что должна делать программа, а искусственный интеллект тут же сгенерирует ее. Узнайте, как создавать и улучшать программы на Python с помощью ИИ, даже если прежде вы не написали ни строчки компьютерного кода. Сэкономьте время на рутинном программировании и воспользуйтесь услугами ИИ, способного мгновенно воплотить ваши идеи в жизнь. Заодно выучите Python!

Название: Ultimate Java for Data Analytics and Machine Learning: Unlock Java's Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j
Автор: Abhishek Kumar
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 529
Язык: английский
Формат: pdf, epub
Размер: 14.1 MB

Empower Your Data Insights with Java's Top Tools and Frameworks. This book is a comprehensive guide to data analysis using Java. It starts with the fundamentals, covering the purpose of data analysis, different data types and structures, and how to pre-process datasets. It then introduces popular Java libraries like WEKA and Rapidminer for efficient data analysis. The middle section of the book dives deeper into statistical techniques like descriptive analysis and random sampling, along with practical skills in working with relational databases (JDBC, SQL, MySQL) and NoSQL databases. It also explores various analysis methods like regression, classification, and clustering, along with applications in business intelligence and time series prediction. The final part of the book gives a brief overview of big data analysis with Java frameworks like MapReduce, and introduces deep learning with the Deeplearning4J library. Whether you're new to data analysis or want to improve your Java skills, this book offers a step-by-step approach with real-world examples to help you master data analysis using Java. This book is ideal for IT professionals, software developers, and data scientists interested in using Java for data analytics. It is also suitable for students and researchers seeking practical insights into Java-based data analysis. Readers should have a basic understanding of Java programming and fundamental concepts in data analysis.

Название: Программирование на Python для начинающих
Автор: Максим Дуплей
Издательство: Stepik
Год: 2024
Формат: PDF
Страниц: много
Размер: 254 Mb
Язык: Русский

Python – это высокоуровневый язык программирования общего назначения с динамической строгой типизацией и автоматическим управлением памятью, ориентированный на повышение производительности разработчика, читаемости кода и его качества, а также на обеспечение переносимости написанных на нём программ.

Название: Windows Native API Programming
Автор: Pavel Yosifovich
Издательство: Leanpub
Год: 2024-06-21
Страниц: 391
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Low-level user-mode programming for Windows usually involves working with the documented Windows API, exported from subsystem DLLs, such as Kernel32.dll, user32.dll, advapi32.dll, kernelbase.dll, and more. Lurking beneath most of these APIs are system calls, invoked under the covers to access the kernel. Anything worthwhile in Windows (or any other OS for that matter) must talk to the kernel to get system-level things done, such as allocating memory, creating processes and threads, performing I/O operations, and more. The native API, implemented in a couple of DLLs is used to make the transition to the kernel. The most important one is NtDll.dll - a system wide user-mode DLL that serves this critical role. This book is about this DLL’s API, as it pertains to invoking system calls that transition the processor to kernel-mode to perform the requested operation. Other APIs discussed are not system calls per-se, but are still part of NtDll, and are interesting to get to know. Most of these functions start with Rtl (Runtime Library). As a simple example, the CreateFile documented Windows API (provided by kernel32.dll) invokes NtCreateFile in NtDll.Dll to ask the kernel to perform the operation. Most of the native APIs are undocumented - hence this book. The sample code for this book can be found on Github. The book is for anyone interested in learning about the Windows native API provided by NtDll.dll. The reader should have a solid understanding of the foundations of Windows, such as processes, threads, virtual memory, and DLLs. Also recommended is a good familiarity of the Windows documented API.

Название: Data Structures for Engineers and Scientists Using Python
Автор: Rakesh Nayak, Nishu Gupta
Издательство: CRC Press
Год: 2025
Страниц: 410
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The text covers the fundamentals of Python programming and the implementation of data structures using Python programming with the help of worked-out examples. It provides a learning tool for engineers as well as for researchers and scientists of advanced level. The text further discusses important concepts such as polynomial manipulation, sparse matrices, implementation of stack using the queue model and topological sorting. A programming language is a formal computer language that is used to send commands and data to a machine. Many languages were created with specific goals in mind, such as data processing and scientific calculations. The Python programming language is a very versatile language that can be used for both data processing and scientific calculations. It is primarily written for senior undergraduate, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering and information technology.

Название: Data mesh в действии
Автор: Майхжак Я., Балноян С., Сивяк М.
Издательство: питер
Год: 2024
Формат: PDF
Страниц: 368
Размер: 23 Mb
Язык: Русский

Потребность эффективно хранить большие объемы данных и обращаться к ним стала одной из ключевых потребностей любого бизнеса. Сетка данных (data mesh) — это новый способ децентрализовать управление данными, радикально повышая их безопасность и доступность. Хорошо спроектированная сетка данных позволяет потреблять данные в режиме самообслуживания и помогает избавляться от узких мест, которые свойственны монолитным архитектурам данных.