Название: Core Java, Volume II: Advanced Features, 13th Edition (Early Release)
Автор: Cay S. Horstmann
Издательство: Oracle Press/Pearson Education
Год: 2024
Страниц: 944
Язык: английский
Формат: epub
Размер: 19.2 MB

The Classic Guide to Advanced Java Programming: Fully Updated for Java 21. Core Java is the leading no-nonsense tutorial and reference for experienced programmers who want to write robust Java code for real-world applications. Now, Core Java, Volume II: Advanced Features, Thirteenth Edition, has been revised to cover the new features and enhancements in the Java 21 long-term support release. As always, all chapters have been completely updated, outdated material has been removed, and the new APIs are covered in detail. This volume focuses on the advanced topics that a programmer needs to know for professional software development and includes authoritative coverage of enterprise programming, networking, databases, security, modularization, internationalization, code processing, and native methods, as well as complete chapters on the Streams, XML, and Date and Time APIs. In addition, the chapters on Swing and Graphics cover techniques that are applicable to both client-side user interfaces and server-side generation of graphics and images. Cay S. Horstmann clearly explains sophisticated new features with depth and completeness and demonstrates how to use them to build professional-quality applications. Horstmann's thoroughly tested sample code reflects modern Java style and best practices. The examples are carefully crafted for easy understanding and maximum practical value, so you can rely on them to jump-start your own programs.

Название: What Is LLMOps? Large Language Models in Production
Автор: Abi Aryan
Издательство: O’Reilly Media, Inc.
Год: 2024-05-03
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Large language models (LLMs), a subcategory of Generative AI, have taken the world by storm. Commonly known for their application in ChatGPT, LLMs have unleashed new energy among developers and businesses looking to integrate AI into their applications. But the internet is also full of disjointed information about LLM applications and how to integrate and deploy them reliably into products and applications. A large language model (LLM) is a statistical model trained on large amounts of text data to emulate human speech for natural language processing (NLP) tasks, such as information extraction, text classification, speech synthesis, summarization, and machine translation. LLMOps, thus, is a framework to automate and streamline large language model (also called a foundational or generative AI model) pipelines. While task-specific models for natural language processing (NLP) have been used in practice for a while, recent advances in NLP have shifted public interest to more task-agnostic models that allow a single model to do all of the tasks listed in the preceding paragraph. LLMs show remarkable performance at programming and coding, due to their capacity for context understanding and syntax awareness. Programming is a highly autoregressive task (i.e., it looks at the previous word to predict the next one), such that code completion is based on previous code elements in the sequence. LLMs, being naturally autoregressive, perform well at autocompleting code snippets to generate syntactically accurate code, drawing on patterns learned from vast repositories of code examples from GitHub or otherwise.

Название: Intelligent Systems of Computing and Informatics
Автор: Samsul Ariffin Abdul Karim, Anand J. Kulkarni, Chin Kim On
Издательство: CRC Press
Год: 2024
Страниц: 354
Язык: английский
Формат: pdf (true)
Размер: 14.3 MB

Since 2011, the Fourth Industrial Revolution (IR4.0) has played a significant role in education, research, and industry. There are nine pillars under the framework of IR4.0 namely Big Data and Analytics, Robotics, Simulation, Horizontal and Vertical Integration, Internet of Things (IoT), Cybersecurity, Cloud Computing, Additive Manufacturing and Augmented Reality. Besides, data technologies have been evolving rapidly to cater the rapid growing size of the data as well as to enhance the security of the shared data through multiple resources and platforms. Machine Learning, IoT, simulation and cloud computing are the mainstream tools to develop an up-to-date Intelligent Systems of Computing and Informatics (ISCI). This new system can be used to produce the desired outcome for the industries through efficient computational intelligence techniques as well as software development. The developments of ISCI are significant as they will enable the related agencies and policy-makers to conduct the quick and reliable self-decision-making involving complex processes in the fields of engineering and computer sciences. Comprising 20 chapters by experts from all over the world, this book covers such topics as data technologies, Machine Learning, signal and image processing, software systems efficiency, computer networking, Internet of Things, and computational intelligence for real-life problems.

Название: Cloud Native Microservices Cookbook: Master the art of microservices in the cloud with over 100 practical recipes
Автор: Varun Yadav
Издательство: BPB Publications
Год: 2024
Страниц: 885
Язык: английский
Формат: pdf, epub
Размер: 21.2 MB

Unlock the secrets of cloud-native success with step-by-step recipes for conquering every stage of microservice deployment. The convergence of microservices and cloud technology represents a significant paradigm shift in software development. To fully leverage the potential of both, integration from the outset of application development is crucial. Cloud-native microservices cookbook serve as a conduit, harmonizing disparate elements of microservice construction by establishing a cohesive framework from inception to deployment. This book meticulously outlines the various stages involved in launching an application utilizing cloud-native microservices. It commences with the foundational aspects of application development, emphasizing microservice architecture principles such as configuration and service discovery, considering cloud infrastructure. Progressing through containerization, continuous integration (CI), and continuous deployment (CD) pipelines, the book explores the intricacies of orchestration, high availability (HA), auto scalability, and cloud security. Subsequently, it elucidates the significance of observability in monitoring microservices post-deployment, concluding with a comprehensive exploration of Infrastructure as Code (IaC) for cloud infrastructure provisioning. Java has been an enterprise grade programming language for more than two decades and has proven to be the best for developing big and highly complex software. The language has evolved a lot from its initial days, has great features and is also quite easy to learn. There are too many practitioners of Java round the globe, and this led to a lot of material getting accumulated freely over the internet on different nuances of programming. Spring Boot is a framework created on top of Spring framework, and is the most matured and tested Java framework for production ready microservices, with enormous support available over the internet.

Название: Microservices for Machine Learning: Design, implement, and manage high-performance ML systems with microservices
Автор: Rohit Ranjan
Издательство: BPB Publications
Год: 2024
Страниц: 966
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Empowering AI innovations: The fusion of microservices and ML. Explore the link between microservices and ML in Microservices for Machine Learning. Through this book, you will learn to build scalable systems by understanding modular software construction principles. You will also discover ML algorithms and tools like TensorFlow and PyTorch for developing advanced models. It equips you with the technical know-how to design, implement, and manage high-performance ML applications using microservices architecture. It establishes a foundation in microservices principles and core ML concepts before diving into practical aspects. You will learn how to design ML-specific microservices, implement them using frameworks like Flask, and containerize them with Docker for scalability. Data management strategies for ML are explored, including techniques for real-time data ingestion and data versioning. This book also addresses crucial aspects of securing ML microservices and using CI/CD practices to streamline development and deployment. Finally, you will discover real-world use cases showcasing how ML microservices are revolutionizing various industries, alongside a glimpse into the exciting future trends shaping this evolving field. Additionally, you will learn how to implement ML microservices with practical examples in Java and Python. This book merges software engineering and AI, guiding readers through modern development challenges. It is a guide for innovators, boosting efficiency and leading the way to a future of impactful technology solutions.

Название: Applications and Principles of Quantum Computing
Автор: Alex Khang
Издательство: IGI Global
Год: 2024
Страниц: 510
Язык: английский
Формат: pdf (true), epub
Размер: 31.3 MB

In a world driven by technology and data, classical computing faces limitations in tackling complex challenges like climate modeling and financial risk assessment. These barriers impede our aspirations to revolutionize industries and solve intricate real-world problems. To bridge this gap, we must embrace quantum computing. Edited by Alex Khang PH, Principles and Applications of Quantum Computing is a transformative solution to this challenge. It delves into the interdisciplinary realms of Computer Science, physics, and mathematics, unveiling the incredible potential of quantum computing, which outperforms supercomputers by 158 million times. This technology, rooted in quantum mechanics, offers solutions to global problems and opens new frontiers in Artificial Intelligence (AI), cybersecurity, finance, drug development, and more. By engaging with this book, you become a pioneer in the quantum revolution, contributing to reshaping the limits of what's achievable in our digital age. Nowadays, quantum computing is a powerful technology both the present and the future, it has the potential to all revolutionize computation for problems solvable in the real life and science researching. While no quantum computer is yet sophisticated and intelligent enough to carry out calculations that a traditional computer can’t does, but hopefully scientists and high-tech companies will be making a great progress soon. With this book, you will be able to learn the key principles of quantum computing such as computation, communication, coordination, recollection, automation, evaluation and design under each perspective on computing, a pathway into the knowledge space of quantum computing and its applications in most areas of Artificial Intelligence science, cybersecurity and cloud-based quantum computing access, etc.

Название: 50 Essential iOS Interview Questions and Answers
Автор: Thien Liu
Издательство: Independently published
Год: 2024
Страниц: 125
Язык: английский
Формат: pdf
Размер: 19.7 MB

Discover 50 essential interview questions that cover various key areas in iOS development. Clear and concise answers to each question, providing you with the knowledge and understanding you need to impress your interviewers. Code snippets and examples to illustrate key concepts and demonstrate practical application of iOS development principles. In Swift, both structs and classes are used to define properties and methods to add functionality. However, there are key differences in how they are used, which stem from Swift's value type (struct) versus reference type (class) distinction. Understanding these differences is crucial for making informed decisions about when to use each in your iOS applications. Object-Oriented Programming (OOP) is a programming paradigm that organizes code into objects, which are instances of classes. OOP focuses on creating classes that encapsulate data and behavior, and objects interact with each other through methods and properties. The main concepts of OOP are encapsulation, inheritance, and polymorphism. On the other hand, Protocol-Oriented Programming (POP) is a programming paradigm that puts protocols at the center of the design. In Swift, protocols define a blueprint of methods, properties, and requirements that conforming types must implement. POP focuses on defining behavior through protocols and then implementing that behavior in concrete types.

Название: Coding Tricks and Tips - 18th Edition, 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 33.8 MB

Coding Tricks and Tips - это идеальное цифровое издание для начинающих программистов, которые хотят поднять свои навыки на новый уровень. Хотите ли вы улучшить свой пользовательский опыт или получить новые знания? Хотите ли вы учиться непосредственно у экспертов в этой области? Хотите узнать бесчисленные сокращения, которыми пользуются профессионалы? На страницах нашего нового руководства для продвинутых пользователей вы узнаете все, что вам нужно знать, чтобы стать более уверенным, компетентным и опытным пользователем. Пользователем, который максимально использует свои навыки программирования. Мы поддерживаем и обучаем вас навыкам, приобретенным за десятилетия опыта, специально для вас.

Название: AI and Common Sense: Ambitions and Frictions
Автор: Martin W. Bauer, Bernard Schiele
Издательство: Routledge
Год: 2024
Страниц: 286
Язык: английский
Формат: pdf (true)
Размер: 13.5 MB

Common sense is the endless frontier in the development of Artificial Intelligence (AI), but what exactly is common sense, can we replicate it in algorithmic form, and if we can – should we? Bauer, Schiele and their contributors from a range of disciplines analyse the nature of common sense, and the consequent challenges of incorporating into Artificial Intelligence models. They look at different ways we might understand common sense and which of these ways are simulated within computer algorithms. These include sensory integration, self-evident truths, rhetorical common places, and mutuality and intentionality of actors within a moral community. How far are these possible features within and of machines? Approaching from a range of perspectives including Sociology, Political Science, Media and Culture, Psychology and Computer Science, the contributors lay out key questions, practical challenges and "common sense" concerns underlying the incorporation of common sense within Machine Learning algorithms for simulating intelligence, socialising robots, self-driving vehicles, personnel selection, reading, automatic text analysis, and text production. A valuable resource for students and scholars of Science–Technology–Society Studies, Sociologists, Psychologists, Media and Culture Studies, human–computer interaction with an interest in the post-human, and programmers tackling the contextual questions of Machine Learning.

Название: Learning PyTorch 2.0: Experiment Deep Learning from basics to complex models using every potential capability of Pythonic PyTorch
Автор: Matthew Rosch
Издательство: GitforGits
Год: 2023
Страниц: 321
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

This book is a comprehensive guide to understanding and utilizing PyTorch 2.0 for Deep Learning applications. It starts with an introduction to PyTorch, its various advantages over other Deep Learning frameworks, and its blend with CUDA for GPU acceleration. We delve into the heart of PyTorch – tensors, learning their different types, properties, and operations. Through step-by-step examples, the reader learns to perform basic arithmetic operations on tensors, manipulate them, and understand errors related to tensor shapes. A substantial portion of the book is dedicated to illustrating how to build simple PyTorch models. This includes uploading and preparing datasets, defining the architecture, training, and predicting. It provides hands-on exercises with a real-world dataset. The book then dives into exploring PyTorch's nn module and gives a detailed comparison of different types of networks like Feedforward, RNN, GRU, CNN, and their combination. Further, the book delves into understanding the training process and PyTorch's optim module. It explores the overview of optimization algorithms like Gradient Descent, SGD, Mini-batch Gradient Descent, Momentum, Adagrad, and Adam. A separate chapter focuses on advanced concepts in PyTorch 2.0, like model serialization, optimization, distributed training, and PyTorch Quantization API. In the final chapters, the book discusses the differences between TensorFlow 2.0 and PyTorch 2.0 and the step-by-step process of migrating a TensorFlow model to PyTorch 2.0 using ONNX.