|
 |
|
 |
|
|
 |
|  |
|
 Название: Enterprise Generative AI Well Architected Framework & Patterns: An Architect's Real-life Guide to Adopting Generative AI in Enterprises at Scale
Автор: Suvoraj Biswas, Moumita Biswas
Издательство: Independently published
Год: 2024
Страниц: 114
Язык: английский
Формат: True/Retail PDF EPUB
Размер: 17.1 MB
Welcome to the "Enterprise Generative AI Well Architected Framework & Patterns" a comprehensive step by step guide designed for Enterprise IT Professionals to explore the cutting-edge world of generative artificial intelligence (AI) systems within the context of enterprise applications. We have all witnessed how OpenAI has recently reshaped the digital landscape through the introduction of tools like ChatGPT, which gained a substantial user base surpassing all popular social media applications. ChatGPT has been powered by what we call Generative AI which not only has remarkable influence in the consumer sphere but also many Enterprises are adopting to solve many business challenges which previously appeared impossible. Generative AI is a form of Deep Learning system which is able to generate new original contents (texts or digital media - audio or Video or images). It uses the Machine Mearning algorithm and artificial neural networks to recognize the underlying pattern in the training data to predict new original contents without any human intervention or influences. This book is intended to provide readers with a clear understanding of the fundamental principles, methodologies, and best practices for implementing generative AI in large-scale enterprise environments. Whether you are a seasoned AI practitioner(Architects, Engineers / Engineering Managers or Product Managers) seeking to deepen your knowledge or an enterprise leader (VPs, CXOs, Founders) exploring the potential of Generative AI for your organization, this book offers valuable insights into leveraging the power of generative models effectively and responsibly. | |
Разместил: Ingvar16 21-04-2024, 07:54 | Комментарии: 0 | Подробнее
| | | |
 |
|  |
|
|
|
|
|
|
| |
|
 Название: Postman Cookbook: Hand-picked Solutions and Techniques across API Design, Testing, Performance, Networking, Kubernetes and Integration
Автор: Oliver James
Издательство: GitforGits
Год: 2024
Страниц: 290
Язык: английский
Формат: pdf, azw3, epub (true), mobi
Размер: 10.1 MB
For developers, programmers, and DevOps engineers venturing into the hard world of API development, the "Postman Cookbook" becomes a must-read. This short solutions book offers recipes and troubleshooting approaches to address typical API lifecycle management challenges. Using Postman's rich features, readers of all skill levels will learn how to create APIs that will improve workflows, increase productivity, and lead to operational success. The book covers a wide range of topics, from the fundamentals of web-based communication to more complex topics including protocol stacks, secure communication protocols, and the dynamics of WebSockets interactions. The following sections cover advanced subjects such as custom protocol handling, network troubleshooting, and proxy management, allowing readers to confidently solve complex networking challenges. This book covers more than simply the technical aspects of Kubernetes. It discusses the influence of security measures, maximizing performance, and successful scaling solutions. These features are critical for microservice architectures and cloud-native apps. This book teaches early developers and programmers the foundations of API testing and development, including networking and protocols. Upon completion of this book, readers will have a thorough understanding of API development with Postman. They will be able to confidently handle the problems of modern computing. | |
Разместил: Ingvar16 20-04-2024, 19:54 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Python for Data Science
Автор: A. Lakshmi Muddana, Sandhya Vinayakam
Издательство: Springer/Ane Books Pvt. Ltd.
Год: 2024
Страниц: 398
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB
The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in Data Science. This book aims to help the readers understand the basic and advanced concepts for developing simple programs and the fundamentals required for building Machine Learning models. The book covers basic concepts like data types, operators, and statements that enable the reader to solve simple problems. As functions are the core of any programming, a detailed illustration of defining & invoking functions and recursive functions is covered. Built-in data structures of Python, such as strings, lists, tuples, sets, and dictionary structures, are discussed in detail with examples and exercise problems. Files are an integrated part of programming when dealing with large data. File handling operations are illustrated with examples and a case study at the end of the chapter. Widely used Python packages for Data Science, such as Pandas, Data Visualization libraries, and regular expressions, are discussed with examples and case studies at the end of the chapters. The book also contains a chapter on SQLite3, a small relational database management system of Python, to understand how to create and manage databases. As AI applications are becoming popular for developing intelligent solutions to various problems, the book includes chapters on Machine Learning and Deep Learning. They cover the basic concepts, example applications, and case studies using popular frameworks such as SKLearn and Keras on public datasets. | |
Разместил: Ingvar16 20-04-2024, 17:34 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Artificial Intelligence: Advances, Ethics, and Strategies
Автор: James M. Nichols
Издательство: Nova Science Publishers
Серия: Computer Science, Technology and Applications
Год: 2024
Страниц: 242
Язык: английский
Формат: pdf (true)
Размер: 25.9 MB
The field of Artificial Intelligence (AI) is rapidly evolving, and one of the most exciting developments in recent years has been the emergence of generative models. These models have shown the ability to produce human-like language and even generate images, videos, and music. While the potential applications of generative models are vast and impressive, there are also serious concerns about the ethical implications of their use. As the potential of AI and generative models is explored, it is essential to consider the impact they may have on society. Generative Artificial Intelligence (GenAI) refers to AI systems, in particular those using Machine Learning (ML) and trained on large volumes of data, that are able to generate new content. In contrast, other AI systems may have a primary goal of classifying data, such as facial recognition image data, or making decisions, such as those used in autonomous vehicles. GenAI systems, when prompted (often by a user inputting text), can create various outputs, including text responses (e.g., OpenAI’s ChatGPT and Google’s Bard), images (e.g., Stability AI’s Stable Diffusion and Midjourney’s self-titled program), videos, computer code, or music. | |
Разместил: Ingvar16 20-04-2024, 16:54 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Artificial Intelligence: Background, Risks and Policies
Автор: Gary Dalton
Издательство: Nova Science Publishers
Серия: Computer Science, Technology and Applications
Год: 2024
Страниц: 280
Язык: английский
Формат: pdf (true)
Размер: 24.2 MB
The field of Artificial Intelligence (AI) has gone through multiple waves of advancement over the decades. Today, AI can broadly be thought of as computerized systems that work and react in ways commonly thought to require intelligence, such as the ability to learn, solve problems, and achieve goals under uncertain and varying conditions. The field encompasses a range of methodologies and application areas, including Machine Learning (ML), natural language processing, and robotics. AI holds potential benefits and opportunities, but also challenges and pitfalls. For example, AI technologies can accelerate and provide insights into data processing; augment human decision-making; optimize performance for complex tasks and systems; and improve safety for people in dangerous occupations. On the other hand, AI systems may perpetuate or amplify bias, may not yet be fully able to explain their decision-making, and often depend on vast datasets that are not widely accessible to facilitate research and development (R&D). Further, stakeholders have questioned the adequacy of human capital in both the public and private sectors to develop and work with AI, as well as the adequacy of current laws and regulations for dealing with societal and ethical issues that may arise. Together, such challenges can lead to an inability to fully assess and understand the operations and outputs of AI systems. | |
Разместил: Ingvar16 20-04-2024, 16:17 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Exploring Operations Research with R
Автор: Jim Duggan
Издательство: CRC Press
Год: 2024
Страниц: 396
Язык: английский
Формат: pdf (true)
Размер: 52.1 MB
Exploring Operations Research with R shows how the R programming language can be a valuable tool – and way of thinking – which can be successfully applied to the field of operations research (OR). This approach is centred on the idea of the future OR professional as someone who can combine knowledge of key OR techniques (e.g., simulation, linear programming, data science, and network science) with an understanding of R, including tools for data representation, manipulation, and analysis. The core aim of the book is to provide a self-contained introduction to R (both Base R and the tidyverse) and show how this knowledge can be applied to a range of OR challenges in the domains of public health, infectious disease, and energy generation, and thus provide a platform to develop actionable insights to support decision making. The central idea behind this book is that R is a valuable computational tool that can be applied to the field of operations research. R provides excellent features such as data representation, data manipulation, and data analysis. You will learn how to program and manipulate data in R, how to harness the power of R’s tidyverse, and observe how R can be used to support problem solving within the field of operations research. The book is primarily aimed at post-graduate students in operations research. With its coverage of R, the tidyverse, and applications in agent-based simulation and system dynamics, the book also supports continuing professional development for operations research practitioners. As R is presented from scratch, there are no prerequisites, although prior experience of a programming language would provide useful contextual knowledge. | |
Разместил: Ingvar16 20-04-2024, 07:07 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Go by Example (MEAP v7)
Автор: Inanc Gumus
Издательство: Manning Publications
Год: 2024
Страниц: 438
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB
Unlock Go’s unique perspective on program design, and start writing simple, maintainable, and testable Go code. Go by Example is a practical guide to writing high-quality code that’s easy to test and maintain. The book is full of best practices to adopt and anti-patterns to dodge. It explores what makes Go so dramatically different from other languages and how you can still leverage your existing skills into writing excellent Go code. Aimed at Go beginners looking to graduate to serious Go development, this book will help you write and test command line applications, web API clients and servers, concurrent programs, and more. Writing well-designed Go code takes more than just porting across skills you’ve learned in other languages. You’ll need to understand Go’s unique way of working to ensure your programs don’t spiral out of control. This book is the perfect primer on Go’s hidden mechanics that will help you code more effective Go. Go by Example teaches you to write well-designed and maintainable code in Go. By concentrating on Go’s unique characteristics, you’ll learn how to stop fighting against the language and start delivering idiomatic code that’s simple, adaptable, and testable. You’ll learn how to deliver applications and how to extend code with robust testing. Easy-to-understand visualizations and step-by-step examples help explain Go’s complexities without oversimplification. To get the most benefit from this book, you’ll need to be an experienced developer with an intermediate knowledge of testing in any language. You may be new to Go, but knowing the basics will help along the way. | |
Разместил: Ingvar16 19-04-2024, 21:50 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Machine Learning with Python: Master Pandas, Scikit-learn, and TensorFlow for Building Smart IA Models
Автор: Joseph T. Handy
Издательство: Independently published
Год: 2024
Страниц: 107
Язык: английский
Формат: pdf, azw3, epub (true), mobi
Размер: 10.1 MB
Machine Learning is revolutionizing the world, and Python is the language of choice for its development. This book equips you with the essential tools - Pandas, Scikit-learn, and TensorFlow - to build and deploy intelligent applications. Written by seasoned practitioners, this book combines clear explanations with practical exercises, helping you gain hands-on experience and build real-world skills. This book, "Machine Learning with Python: Master Pandas, Scikit-learn, and TensorFlow for building Smart AI Models," is your passport to this thrilling world. Through an exciting journey filled with practical exercises, real-world examples, and a dash of humour, you'll not just understand the fundamentals of ML, but also become proficient in using powerful Python libraries like Pandas, Scikit-learn, and TensorFlow to build your own intelligent systems. No prior coding experiences? No worries! We'll walk you through the necessary Python basics, ensuring you have a solid foundation before diving into the heart of ML. So, what are you waiting for? Buckle up, grab your favourite coding buddy (or just grab a cup of coffee!), and get ready to unleash the power of machine learning! In the first chapter, we'll unveil the fascinating world of ML, exploring its various applications and why Python reigns supreme in this domain. We'll also set up your learning environment, so you can start coding right away. | |
Разместил: Ingvar16 19-04-2024, 20:24 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: Python Essentials 1: The Official OpenEDG Python Institute beginners course with practical exercises – learn the basics of Python in seven days and pass the PCEP certification exam
Автор: The OpenEDG Python Institute
Издательство: The OpenEDG Python Institute
Серия: Python Essentials
Год: 2023
Страниц: 515
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB
Unleash Your Potential and Transform Your Life with Python Essentials 1 — Your Gateway to Career Success! Are you stuck in a job that drains your energy? Do you yearn to achieve your full potential, all while earning a better income? Are you overwhelmed by repetitive, tedious tasks that eat away at your free time and joy? Step into a transformative learning experience with Python Essentials 1 — a meticulously crafted course that empowers you to claim the life you've always wanted. This book doesn't just teach you Python; it opens the door to a thrilling career as a professional programmer, and an opportunity to become part of a global community of people just like you. Every moment you invest in learning equips you to tackle real-world challenges with Python, setting you on a fast-track to becoming an in-demand professional. Python is one of the fastest growing programming languages in the world, and is used in almost every sector and industry, from gaming, to medicine, to nuclear physics. It is essential for any would-be programmer to have at least a foundational knowledge of Python. Luckily, Python is also one of the easiest programming languages to learn. With its focus on real-world words and syntax, a beginner learner of Python can start writing simple programs within minutes. All the code examples in the book have been tested on Python 3.4, 3.6, 3.7, 3.8, and 3.9, and should work with any subsequent versions of Python 3.x. | |
Разместил: Ingvar16 19-04-2024, 19:15 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 Название: New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms
Автор: Patricia Melin, Oscar Castillo
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2024
Страниц: 204
Язык: английский
Формат: pdf (true), epub
Размер: 35.6 MB
We describe in this book new directions on the theoretical developments of fuzzy logic, neural networks, and meta-heuristic algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. There are papers with the main topics from type-1 to type-3 fuzzy logic, which basically consists of a group of papers that propose new concepts and algorithms based on type-1, type-2, and type-3 fuzzy logic and their applications. There are also papers that present the theory and practice of meta-heuristics in diverse application areas. There are interesting papers on different applications of fuzzy logic, neural networks, and hybrid intelligent systems in medical problems. In addition, we can find papers describing applications of fuzzy logic, neural networks, and meta-heuristics in robotics problems. Another set of papers presents the theory and practice of neural networks in diverse application areas, including convolutional and deep learning neural networks. There are also a group of papers that present the theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, we can find a group of papers describing the applications of fuzzy logic, neural networks, and meta-heuristics in pattern recognition problems. In conclusion, the edited book comprises contributions on diverse aspects of fuzzy logic, neural networks, and optimization of meta-heuristic algorithms for designing optimal hybrid intelligent systems and their application in areas such as intelligent control and robotics, pattern recognition, decision-making, time series prediction, and optimization of complex problems. | |
Разместил: Ingvar16 19-04-2024, 17:45 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
Навигация
Вход на сайт
Реклама
