Название: CodeMosaic: Learn AI-Driven Development and Modern Best Practices for Enterprise
Автор: Arpit Dwivedi
Издательство: Apress
Год: 2024
Страниц: 559
Язык: английский
Формат: pdf, epub
Размер: 24.4 MB

This book is a comprehensive guide for those navigating through the complexities of enterprise software development. For fresh graduates, transitioning from college projects to real-world applications can be overwhelming. This book acts as a roadmap, helping you bridge the gap to become industry-ready. It's like an intensive internship in book form, equipping readers with the skills and knowledge needed for modern tech roles. But it's not just for newcomers. Even experienced developers can get caught up in old routines and miss out on new tools and techniques. With the rise of AI and automation tools like ChatGPT and Copilot, the development landscape is rapidly changing. The core of the book revolves around practical application. Using .NET, Angular, and other Microsoft technologies as foundational pillars, you’ll embark on a hands-on journey. From understanding the basics to designing and deploying a full-stack web application, CodeMosaic offers a holistic learning experience. By the end, you won't just be a developer; you'll be well-equipped to tackle the challenges of today's digital world. For experienced developers looking for new tools and techniques, and recent graduates, transitioning from college projects to real-world applications.

Название: Statistical Prediction and Machine Learning
Автор: John Tuhao Chen, Lincy Y. Chen, Clement Lee
Издательство: CRC Press
Год: 2024
Страниц: 315
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Written by an experienced statistics educator and two data scientists, this book unifies conventional statistical thinking and contemporary Machine Learning framework into a single overarching umbrella over Data Science. The book is designed to bridge the knowledge gap between conventional statistics and Machine Learning. It provides an accessible approach for readers with a basic statistics background to develop a mastery of Machine Learning. The book starts with elucidating examples in Chapter 1 and fundamentals on refined optimization in Chapter 2, which are followed by common supervised learning methods such as regressions, classification, support vector machines, tree algorithms, and range regressions. After a discussion on unsupervised learning methods, it includes a chapter on unsupervised learning and a chapter on statistical learning with data sequentially or simultaneously from multiple resources. When addressing practical problems such as high dimensional inference, Machine Learning often relies on computer intensive algorithms. Many of the underlying thought processes and methodologies have been well-developed but are still fundamentally based in the conventional data analysis framework. One of the major challenges underpinning modern Machine Learning stems from the gap between the conventional model-based inference and data-driven learning algorithms. The knowledge gap hinders practitioners (especially students, researchers, data analysts, or consultants) from truly mastering and correctly applying Machine Learning skills in Data Science. This book is addressed to practitioners in Data Science, but it is also suitable for upper-level undergraduate students and entry-level graduate students who are interested in obtaining a more thorough comprehension of Machine Learning.

Название: Applied Text Mining
Автор: Usman Qamar, Muhammad Summair Raza
Издательство: Springer
Год: 2024
Страниц: 505
Язык: английский
Формат: pdf (true)
Размер: 12.9 MB

This textbook covers the concepts, theories, and implementations of text mining and Natural Language Processing (NLP). It covers both the theory and the practical implementation, and every concept is explained with simple and easy-to-understand examples. It consists of three parts. In Part 1 which consists of three chapters details about basic concepts and applications of text mining are provided, including eg sentiment analysis and opinion mining. It builds a strong foundation for the reader in order to understand the remaining parts. In the five chapters of Part 2, all the core concepts of text analytics like feature engineering, text classification, text clustering, text summarization, topic mapping, and text visualization are covered. Finally, in Part 3 there are three chapters covering deep-learning-based text mining, which is the dominating method applied to practically all text mining tasks nowadays. Various Deep Learning approaches to text mining are covered, includingmodels for processing and parsing text, for lexical analysis, and for machine translation. All three parts include large parts of Python code that shows the implementation of the described concepts and approaches. The textbook was specifically written to enable the teaching of both basic and advanced concepts from one single book. The implementation of every text mining task is carefully explained, based Python as the programming language and Spacy and NLTK as Natural Language Processing libraries. No prior knowledge of Python, Spacy, and NLTK is required. The book is suitable for both undergraduate and graduate students in Computer Science and engineering, who wish to study and learn more on this important active discipline that is considered an important milestone in Artificial Intelligence (AI). The book focuses in a unique style on looking at Generative AI to generate, understand, and interpret text.

Название: jаvascript for Automation 3: More Useful and Interesting Scripts
Автор: Jesse Shanks
Издательство: Aquitaine Publishing
Год: 2024
Язык: английский
Формат: epub
Размер: 10.1 MB

Unlock the power of automation and enhance your productivity with "jаvascript for Automation 3: More Useful and Interesting Scripts" This collection dives into the practical applications of jаvascript for Automation (JXA) on macOS, providing you with a wealth of knowledge to streamline your workflows and tackle complex tasks effortlessly. Integrating with ChatGPT, APIs, Mac Applications, between devices are all available with scripts. Whether you're a seasoned developer or a beginner, this book offers step-by-step instructions and real-world examples to help you harness the full potential of JXA. Each chapter is packed with insightful examples and practical tips, making complex automation tasks accessible and enjoyable. Whether you're looking to streamline your workflow, enhance your coding skills, or simply explore the fascinating world of JXA programming, this book is your ultimate guide to achieving more with your Mac. Embark on your automation journey today and transform the way you work with "jаvascript for Automation 3: More Useful and Interesting Scripts."

Название: Digital Image Denoising in MATLAB
Автор: Chi-Wah Kok, Wing-Shan Tam
Издательство: Wiley-IEEEPress
Год: 2024
Страниц: 227
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Presents a review of image denoising algorithms with practical MATLAB implementation guidance. Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such as array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB, this hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book. The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions. Digital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques.

Название: FastAPI: веб-разработка на Python
Автор: Билл Любанович
Издательство: Спринт Бук
Год: 2024
Формат: pdf, epub
Размер: 28 Мб
Качество: Хорошее
Язык: Русский

FastAPI — относительно новый, но надежный фреймворк с чистым дизайном, использующий преимущества актуальных возможностей Python. Как следует из названия, FastAPI отличается высоким быстродействием и способен конкурировать в этом с аналогичными фреймворками на таких языках, как Golang. Эта практическая книга расскажет разработчикам, знакомым с Python, как FastAPI позволяет достичь большего за меньшее время и с меньшим количеством кода.

Название: Tensorflow for Quantitative Finance: Transform Financial Analysis with TensorFlow's Cutting-Edge Machine Learning Techniques (Python Libraries for Finance)
Автор: Hayden Van Der Post
Издательство: Reactive Publishing
Год: 2024
Страниц: 578
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Transform your financial analysis and modeling with "TensorFlow for Quantitative Finance," the ultimate guide for financial professionals seeking to harness the power of Machine Learning. This comprehensive book equips financial analysts, data scientists, and quantitative researchers with the tools and knowledge to apply TensorFlow's advanced capabilities to a wide range of financial applications. Explore how TensorFlow can revolutionize financial modeling, from predictive analytics to risk management and algorithmic trading. This expert-level resource provides practical, hands-on examples, detailed tutorials, and real-world case studies to help you integrate TensorFlow into your quantitative finance workflows effectively. With contributions from leading industry experts, this book offers insights into the latest advancements in financial technology and practical guidance on applying TensorFlow to solve complex financial problems. Enhance your analytical skills, make data-driven decisions, and stay competitive in the evolving financial landscape with "TensorFlow for Quantitative Finance.

Название: Binary Representation Learning on Visual Images: Learning to Hash for Similarity Search
Автор: Zheng Zhang
Издательство: Springer
Год: 2024
Страниц: 210
Язык: английский
Формат: pdf (true), epub
Размер: 50.2 MB

This book introduces pioneering developments in binary representation learning on visual images, a state-of-the-art data transformation methodology within the fields of Machine Learning and multimedia. Binary representation learning, often known as learning to hash or hashing, excels in converting high-dimensional data into compact binary codes meanwhile preserving the semantic attributes and maintaining the similarity measurements. In this book, we provide a comprehensive introduction to the theories, algorithms, and applications that cover the latest research in hashing-based visual image retrieval, with a focus on binary representations. These representations are crucial in enabling fast and reliable feature extraction and similarity assessments on large-scale data. This book offers an insightful analysis of various research methodologies in binary representation learning for visual images, ranging from basis shallow hashing, advanced high-order similarity-preserving hashing, deep hashing, as well as adversarial and robust deep hashing techniques. These approaches can empower readers to proficiently grasp the fundamental principles of the traditional and state-of-the-art methods in binary representations, modeling, and learning. The theories and methodologies of binary representation learning expounded in this book will be beneficial to readers from diverse domains such as Machine Learning, multimedia, social network analysis, web search, information retrieval, data mining, and others.

Название: Deep Learning and Computational Physics
Автор: Deep Ray , Orazio Pinti , Assad A. Oberai
Издательство: Springer
Год выхода: 2024
Страниц: 160
Формат: True PDF
Размер: 10,1 MB
Язык: английский

The main objective of this book is to introduce a student who is familiar with elementary math concepts to select topics in deep learning. It exploits strong connections between deep learning algorithms and the techniques of computational physics to achieve two important goals. First, it uses concepts from computational physics to develop an understanding of deep learning algorithms. Second, it describes several novel deep learning algorithms for solving challenging problems in computational physics, thereby offering someone who is interested in modeling physical phenomena with a complementary set of tools. It is intended for senior undergraduate and graduate students in science and engineering programs. It is used as a textbook for a course (or a course sequence) for senior-level undergraduate or graduate-level students.

Название: Agile-SOFL Agile Formal Engineering Method
Автор: Shaoying Liu
Издательство: Springer
Год выхода: 2024
Страниц: 154
Формат: True PDF
Размер: 14,4 MB
Язык: английский

This book describes a specific solution, known as Agile-SOFL, for bridging agile and formal engineering and discusses its benefits for realistic software projects. In this book, the author argues that formal engineering methods and agile approaches are complementary in ensuring high productivity while enhancing reliability. Agile-SOFL offers a highly practical and systematic method that strikes a good balance of efforts for enhancing both software productivity and reliability. Specifically, Agile-SOFL is characterized by five features: (1) systematic approach to constructing hybrid specifications for requirements-related faults prevention, (2) specification-based incremental programming for quality implementation, (3) specification-based inspection and testing for system validation, (4) automatic testing-based formal verification for the correctness of code, and (5) effective project management for high effectiveness and efficiency in applying Agile-SOFL.