Название: Quarkus in Action (MEAP v8)
Автор: Martin Stefanko, Jan Martiska
Издательство: Manning Publications
Год: 2024
Страниц: 702
Язык: английский
Формат: pdf, epub
Размер: 14.6 MB

Build resilient and scalable, cloud-native, enterprise Java applications using the Quarkus framework. Quarkus in Action teaches you to build resilient and scalable cloud applications with Quarkus. It's written by Martin Stefanko and Jan Martiska, Red Hat engineers who are both active contributors to the Quarkus project. Working hands-on through a realistic business application, you'll use Quarkus to simplify the development process of a car rental application. Learn how Quarkus lets you live-reload your Java code, deliver continuous background testing, and automatically provide database instances, plus tons more productivity-boosting features. Quarkus is a Java framework that targets microservices and serverless system development. Quarkus emerged as an alternative to the existing Java microservices stacks to provide an application framework that delivers an unmatched performance benefits while still providing a development model utilizing the APIs (Application-Programming interfaces) of popular libraries and Java standards that the Java ecosystem has been practicing for years. Quarkus also puts a strong focus on developer productivity because, as developers know a technology’s productivity and usability are what is appreciated the most.

Название: AI iQ for a Human-Focused Future: Strategy, Talent, and Culture
Автор: Seth Dobrin
Издательство: CRC Press
Серия: Chapman & Hall/CRC Artificial Intelligence and Robotics Series
Год: 2025
Страниц: 265
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

AI iQ for a Human-Focused Future: Strategy, Talent, and Culture offers a pioneering approach to integrating Artificial Intelligence (AI) and Generative AI (GenAI) in business, emphasizing a business strategy first mindset over a technology-centric one. The book challenges the usual hype surrounding AI, advocating for a more realistic perspective. It delves into the evolution of AI, from traditional Data Science and Machine Learning to GenAI, all through the lens of strategic business application. Unlike other texts, it moves away from case studies, favoring practical, real-world advice from extensive field experience. The book presents strategies for creating an environment that not only accepts but thrives on AI, focusing on strategic leadership, talent development, and inclusivity. It highlights crucial roles, such as the Chief AI Officer, and emphasizes the importance of diversity in AI teams. In November 2022, GenAI took off when OpenAI released ChatGPT. This conversational interface allows anyone who can type or speak to interact with the model. ChatGPT was initially a front end for GPT-3 (Generative Pre-trained Transformer version 3). GenAI is not a new technology. ChatGPT is merely a way for the public to use GenAI. Like statistics, Machine Learning, and Deep Learning, GenAI is part of a hierarchy as well. The base of the hierarchy is Deep Learning. The first layer under that is a concept known as foundation models. These Deep Learning models are pre-trained on an extensive data set (in the case of ChatGPT, a considerable portion of the internet). Foundation models train on a specific domain. Then, one can apply the model to their proprietary data to get the power of the extensive data without having the data, the skill, or the resources it took to build the foundation model. GenAI is a foundation model pre-trained on vast data sets to generate new data. GenAI comes in multiple flavors: language, speech, text, image, video, 3D images, and scientific-focused models (genetics, chemistry, pharmaceuticals, etc.). To sum this up. ChatGPT is a large language model, a kind of GenAI, and various foundation models, Deep Learning, and Machine Learning models, all based on statistics.

Название: C++ Compiler Construction: Mastering Language Processing
Автор: Theophilus Edet
Издательство: CompreQuest Books
Серия: Computer Science Fundamentals
Год: 2024
Страниц: 520
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Are you ready to delve into the fascinating world of compiler construction? Look no further than "C++ Compiler Construction: Mastering Language Processing" by Theophilus Edet. This comprehensive guide is designed to captivate the attention of developers, educators, and enthusiasts alike, offering an in-depth exploration of the intricate process of building compilers for the C++ programming language. Why Build Compilers with C++? C++, renowned for its power, flexibility, and performance, serves as an ideal choice for building compilers. As a high-level programming language with low-level capabilities, C++ offers developers a robust set of features and abstractions for expressing complex ideas and solving a diverse range of problems. Its rich standard library, support for various programming paradigms, and efficient memory management make it well-suited for implementing the intricate logic and optimizations required in compiler construction. Moreover, leveraging C++ for compiler development enables developers to write compilers that are not only efficient and reliable but also portable across different platforms and architectures. Understanding compiler construction is invaluable for developers, as compilers play a pivotal role in the software development lifecycle. Whether developing applications, libraries, or systems software, developers rely on compilers to translate their high-level code into executable machine instructions. By delving into the intricacies of compiler design and implementation, developers gain a deeper understanding of programming languages, memory management, optimization techniques, and system architecture.

Название: ActivityPub: Programming for the Social Web (4th Early Release)
Автор: Evan Prodromou
Издательство: O’Reilly Media, Inc.
Год: 2024-05-02
Страниц: 327
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

ActivityPub is the new standard for connecting social networks together on the social web. This open, decentralized social networking protocol defines an API for sharing activities to a social network and a procedure that servers use to distribute those activities to a subscriber's feed. With this book, you'll learn how to assemble ActivityPub-enabled clients for making new kinds of social apps on top of existing networks and build ActivityPub servers that create new human or automated accounts on the social web. With those skills under your belt, you can explore other applications of this publish-subscribe technology: content management systems, internet of things, and enterprise automation. With hands-on examples and in-depth knowledge from Evan Prodromou, one of the authors of the protocol, this is the ActivityPub handbook that every social software hacker needs. The goal of this book is to teach you how to use the standards of the social web to make cool software and help human beings connect in fascinating ways. You can use social web technologies to connect an existing project to the social web, or you can start something new from scratch. You can make a tool that only a few people will use or something that changes how people live their lives, online and off. Let’s take a quick look at the main relevant standards for social web software: Activity Streams 2.0 for data, the ActivityPub federation protocol for server interconnection, and the ActivityPub API for client-to-server programming.

Название: Signal Processing with Python: A Practical Approach
Автор: Irshad Ahmad Ansari, Varun Bajaj
Издательство: IOP Publishing
Год: 2024
Страниц: 297
Язык: английский
Формат: pdf (true)
Размер: 59.5 MB

This book explores the domain of signal processing using Python, with the help of working examples and accompanying code. The book introduces the concepts of Python programming via signal processing with numerous hands-on examples and code snippets. The book will enable readers to appreciate the power of Python in this field and write their code to implement complex signal processing algorithms such as signal compression, cleaning, segmentation, decomposition, and feature extraction and be able to incorporate machine learning models using relevant Python libraries. This book aims to bring together professionals from academia and industry to ignite new developments and techniques in the domain of signal processing with Python. Python, being an open source and popular language, has attracted a lot of application development. Signal processing has also seen tremendous growth in the recent past. The majority of signal processing work revolves around simulation and testing before the final hardware implementation. Many times, code-based implementation itself is sufficient. These implementations make use of a cloud processing unit for a faster and more efficient user experience. Python has been developed as a tool for simulation, visualization, understanding, and manipulation of signals. We will use Python libraries MNE, NumPy, Matplotlib, and Pandas to preprocess and make data usable for further Machine Learning algorithms and models.

Название: Introduction to Data Science in Biostatistics: Using R, the Tidyverse Ecosystem, and APIs
Автор: Thomas W. MacFarland
Издательство: Springer
Год: 2024
Страниц: 536
Язык: английский
Формат: pdf (true)
Размер: 21.5 MB

Introduction to Data Science in Biostatistics: Using R, the Tidyverse Ecosystem, and APIs defines and explores the term "Data Science" and discusses the many professional skills and competencies affiliated with the industry. With Data Science being a leading indicator of interest in STEM fields, the text also investigates this ongoing growth of demand in these spaces, with the goal of providing readers who are entering the professional world with foundational knowledge of required skills, job trends, and salary expectations. The text provides a historical overview of computing and the field's progression to R as it exists today, including the multitude of packages and functions associated with both Base R and the tidyverse ecosystem. Readers will learn how to use R to work with real data, as well as how to communicate results to external stakeholders. A distinguishing feature of this text is its emphasis on the emerging use of APIs to obtain data. This text was developed to assist beginning students and early stages researchers in their attempt to make sense of how software can be used in biostatistics, viewing an all-pervasive concept of biostatistics in the large and the many disciplines associated with biostatistics. To meet this challenge, R was selected as the most appropriate programming language, calling on Base R (e.g., the many functions made available when R is first downloaded) and supporting packages (e.g., the thousands of auxiliary R software collections that provide functionality far beyond what is available in Base R, especially packages associated with the Tidyverse ecosystem).

Название: Python Tkinter 35 Mini Projects : Practical guide for begineer
Автор: Vaishali B. Bhagat
Издательство: Independently published
Год: 2024
Страниц: 218
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Dive into the world of Python GUI programming with Tkinter through 35 exciting mini projects! Perfect for beginners and those looking to enhance their skills, this book offers a hands-on approach to learning. From creating simple interfaces to building interactive applications, each project is designed to help you grasp Tkinter concepts effortlessly. With clear explanations and practical examples, you'll gain confidence in GUI development while unleashing your creativity. Start your journey today and discover the power of Python Tkinter! Welcome to our Tkinter tutorial! In this program, we'll explore how to make a simple graphical user interface (GUI) using Python Tkinter. Our aim is to build a program that greets users with a welcome message when they click a button. To do this, we'll be using Tkinter, the most popular library for making GUIs in Python. We'll use two widgets: a Button labeled "Click Me" and a Label to display the text. Initially, the label won't show any text. However, when the button is clicked, it will update to show the message "Welcome to Python Programming world!" in a bold font. Let's dive in and create our first Tkinter app! Requirements: Text Editor or IDE: You'll need a text editor to write the code. I've used the Thonny IDE for writing and executing this program. However, you can use any Python IDE or text editor of your choice to run the program.

Название: Practical Python Backend Programming: Build Flask and FastAPI applications, asynchronous programming, containerization and deploy apps on cloud
Автор: Tim Peters
Издательство: GitforGits
Год: 2024
Страниц: 431
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

"Practical Python Backend Programming" is a quick pragmatic book that teaches both new and experienced developers the fundamentals of backend development with Python. All sorts of developers, from Python programmers to non-Python programmers, full stack developers, and web developers, will find what they need to know to become experts in backend programming in this entire book. The book covers key topics in backend development, including how to set up stable development environments and how to use virtual environments for better dependency management. With this book, readers will have a firm grasp of Python programming with an emphasis on backend tasks by learning the language's syntax, data structures, and functions. The book teaches you to create and launch dynamic web apps by providing an in-depth look at web frameworks such as Flask and FastAPI. It teaches SQLAlchemy for efficient data handling and advanced database integration, and it shows to improve applications with databases like PostgreSQL, MySQL, and MongoDB. Strategies for managing concurrent operations and improving performance are also covered in the book, along with asynchronous programming in Python. This book delves into various authentication methods, secure communication protocols such as HTTPS, and techniques to secure REST APIs. For efficient management of asynchronous tasks and real-time data processing, it also introduces message brokers such as RabbitMQ and Kafka. The book teaches its readers how to containerize apps and manage them on a large scale by integrating technologies like Docker and Kubernetes.

Название: Ethics, Machine Learning, and Python in Geospatial Analysis
Автор: Mohammad Gouse Galety, Arul Kumar Natarajan, Tesfaye Fufa Gedefa, Tsegaye Demsis Lemma
Издательство: IGI Global
Год: 2024
Страниц: 359
Язык: английский
Формат: pdf (true), epub
Размер: 26.8 MB

In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and Machine Learning. The book's meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques. The chapters within this book span a diverse range of topics, each meticulously crafted to provide readers with a holistic understanding of the subject matter. From examining the ethical dimensions of GIS data privacy to mastering geospatial analysis with Python, each Chapter contributes to a nuanced field exploration. Further, prominent Python libraries for geospatial analysis are explored. GeoPandas is introduced, detailing its capabilities in working with geospatial data, handling geometric data structures, and leveraging spatial operations. Shapely is examined for its role in geometric manipulations. Fiona is explored as a library for handling geospatial data.

Название: Fundamental Mathematical Concepts for Machine Learning in Science
Автор: Umberto Michelucci
Издательство: Springer
Год: 2024
Страниц: 259
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

This book is for individuals with a scientific background who aspire to apply Machine Learning (ML) within various natural science disciplines—such as physics, chemistry, biology, medicine, psychology and many more. It elucidates core mathematical concepts in an accessible and straightforward manner, maintaining rigorous mathematical integrity. For readers more versed in mathematics, the book includes advanced sections that are not prerequisites for the initial reading. It ensures concepts are clearly defined and theorems are proven where it's pertinent. Machine Learning transcends the mere implementation and training of algorithms; it encompasses the broader challenges of constructing robust datasets, model validation, addressing imbalanced datasets, and fine-tuning hyperparameters. These topics are thoroughly examined within the text, along with the theoretical foundations underlying these methods. Rather than concentrating on particular algorithms this book focuses on the comprehensive concepts and theories essential for their application. It stands as an indispensable resource for any scientist keen on integrating Machine Learning effectively into their research. Numerous texts delve into the technical execution of Machine Learning algorithms, often overlooking the foundational concepts vital for fully grasping these methods. This leads to a gap in using these algorithms effectively across diverse disciplines. Although the book does not delve into programming details, it points out its relevance in Machine Learning, especially considering Python.