Название: Essential Guide to React for All Levels
Автор: Аdеоlu О.
Издательство: Young M. Computer Guru Institute
Серия: 2024 Collection: Forging Ahead in Tech and Programming
Год: 2023
Страниц: 194
Язык: английский
Формат: epub
Размер: 15.6 MB

Whether you're a beginner or a seasoned developer, this comprehensive guide will take you on a journey through React's powerful ecosystem. React is an open-source javascript library used for building user interfaces (UIs) in web applications. It was developed by Facebook and was later released as an open-source project. React allows developers to create reusable UI components that can be combined to build complex and interactive web applications. At its core, React uses a declarative approach to building UIs. Instead of manipulating the DOM directly, developers describe how the UI should look at any given point in time, and React takes care of updating the actual DOM efficiently. React uses a virtual DOM (a lightweight representation of the actual DOM) to optimize performance. When there are changes in the application's state or props, React compares the virtual DOM with the real DOM and only updates the necessary parts, minimizing the number of actual DOM manipulations. This approach makes React highly efficient and helps in creating fast and responsive user interfaces. Whether you're building web applications or mobile apps, this guide equips you with the knowledge and techniques to create exceptional React-powered experiences. With in-depth explanations and practical examples, the "Essential Guide to React for All Levels" is your go-to resource for mastering React development.

Название: Python For Financial Analysis: From Zero to Hero (Python for Finance)
Автор: Науdеn Vаn Dеr Роst
Издательство: Reactive Publishing
Год: 2023
Страниц: 157
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

From the Boardroom to the Trading Floor: Discover Python's Power in Finance. In the bustling world of finance, staying ahead is not just an advantage – it's a necessity. Dive into a riveting journey from the ground up, as we unlock Python's potential in financial analysis. Tailored for professionals, yet crafted with the passion of a storyteller, this guide promises more than just coding lessons – it's your gateway to financial mastery. Choosing the right tool for a specific task is always a crucial decision. When it comes to financial analysis, that decision becomes even more vital as it impacts efficiency, precision, and the potential for innovative practices. Python, a general-purpose language that has become a mainstay in the world of financial analysis, fits the bill perfectly. The potent combination of Python with its highly useful libraries further amplifies its applicability in finance. Libraries like NumPy and pandas serve as potent tools for numerical computations and data analysis. Meanwhile, libraries like Matplotlib and Seaborn simplify data visualization, a key aspect of financial analysis. Moreover, the open-source nature of Python means that this list of powerful libraries only continues to grow and evolve. Python also shines in its ability to integrate with different data sources, a crucial facet for financial analysts, considering they often work with vast amounts of data coming from disparate sources. Python's effective API integrations allow for seamless data retrieval, whether it's from databases, other programming languages, or direct online sources.

Название: Generative AI : Navigating the Course to the Artificial General Intelligence Future
Автор: Маrtin Мusiоl
Издательство: Wiley
Год: 2024
Страниц: 435
Язык: английский
Формат: pdf (true), epub
Размер: 28.6 MB

An engaging and essential discussion of generative Artificial Intelligence. In Generative AI: Navigating the Course to the Artificial General Intelligence Future, celebrated author Martin Musiol―founder and CEO of generativeAI.net and GenAI Lead for Europe at Infosys―delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space. Musiol analyzes complex and foundational topics in generative AI, breaking them down into straightforward and easy-to-understand pieces. AI can perform tasks ranging from predefined expert answers, also known as expert systems, to tasks that require human-level intelligence. Think about recognizing speech and images, understanding natural language processing (NLP), making sophisticated decisions, and solving complex problems. For tasks like this, the AI has to train on a respective dataset until it is able to perform the desired activity as well as possible. This self-learning part of AI is referred to as machine learning (ML). Because most of the interesting applications are happening through machine learning in one way or another, and to keep it simple, we use AI and ML interchangeably.

Название: Machine Learning in Medical Imaging and Computer Vision
Автор: Аmitа Nаndаl, Liаng Zhоu, Аrvind Dhаkа, Тоdоr Gаnсhеv
Издательство: The Institution of Engineering and Technology
Год: 2024
Страниц: 382
Язык: английский
Формат: pdf (true)
Размер: 21.1 MB

Medical images can highlight differences between healthy tissue and unhealthy tissue and these images can then be assessed by a healthcare professional to identify the stage and spread of a disease so a treatment path can be established. With Machine Learning techniques becoming more prevalent in healthcare, algorithms can be trained to identify healthy or unhealthy tissues and quickly differentiate between the two. Statistical models can be used to process numerous images of the same type in a fraction of the time it would take a human to assess the same quantity, saving time and money in aiding practitioners in their assessment. This edited book discusses feature extraction processes, reviews Deep Learning methods for medical segmentation tasks, outlines optimisation algorithms and regularisation techniques, illustrates image classification and retrieval systems, and highlights text recognition tools, game theory, and the detection of misinformation for improving healthcare provision. Machine Learning in Medical Imaging and Computer Vision provides state of the art research on the integration of new and emerging technologies for the medical imaging processing and analysis fields. This book outlines future directions for increasing the efficiency of conventional imaging models to achieve better performance in diagnoses as well as in the characterization of complex pathological conditions. Medical imaging is increasingly using Machine Learning and computer vision. Deep Learning allows convolutional neural networks (CNNs) to classify, segment, and identify medical images. This has allowed the creation of new tools and apps to aid in illness detection and treatment. This discipline studies deep learning-enabled medical computer vision, Machine Learning for medical image analysis, and personalized medicine using image processing, computer vision, and Machine Learning.

Название: Professional C++, 6th Edition
Автор: Маrс Grеgоirе
Издательство: Wiley
Год: 2024
Страниц: 1379
Язык: английский
Формат: pdf (true), epub
Размер: 16.9 MB

Expand your C++ toolkit quickly and efficiently with this advanced resource. In the newly revised sixth edition of Professional C++, veteran software engineer and developer Marc Gregoire delivers yet another volume that raises the bar for advanced programming manuals. Covering the major new revisions contained in the new C++ standard codenamed C++23, the book offers case studies with working code that’s been tested in Windows and Linux. All in all, with the release of C++23 in 2023, C++ is almost 40 years old and still going strong. In most rankings of programming languages in 2023, C++ is in the top four. It is being used on an extremely wide range of hardware, going from small devices with embedded microprocessors all the way up to multi-rack supercomputers. Besides wide hardware support, C++ can be used to tackle almost any programming job, be it games on mobile platforms, performance-critical artificial intelligence (AI) and machine learning (ML) software, components for self-driving cars, real-time 3-D graphics engines, low-level hardware drivers, entire operating systems, software stacks for networking equipment, web browsers, and so on. The performance of C++ programs is hard to match with any other programming language, and as such, it is the de facto language for writing fast, powerful, and enterprise-class programs. Even if you have used the language for years, you might still be unfamiliar with the more advanced features of C++, or you might not be using the full capabilities of the language. Maybe you don't yet know all the new features introduced with the latest release, C++23. Perhaps you write competent C++ code but would like to learn more about design and good programming style in C++. Or maybe you're relatively new to C++ but want to learn the “right” way to program from the start. This book will meet those needs and bring your C++ skills to the professional level.

Название: Computer Vision: Object Detection In Adversarial Vision
Автор: Мrinаl Каnti Вhоwmik
Издательство: CRC Press
Год: 2024
Страниц: 209
Язык: английский
Формат: pdf (true)
Размер: 81.2 MB

This comprehensive textbook presents a broad review of both traditional (i.e., conventional) and Deep Learning aspects of object detection in various adversarial real-world conditions in a clear, insightful, and highly comprehensive style. Beginning with the relation of computer vision and object detection, the text covers the various representation of objects, applications of object detection, and real-world challenges faced by the research community for object detection task. The book addresses various real-world degradations and artifacts for the object detection task and also highlights the impacts of artifacts in the object detection problems. The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks. The book also collects together solutions and perspectives proposed by the preeminent researchers in the field, addressing not only the background of visibility enhancement but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative real-world challenges. Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness. It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging real-world conditions. Contains various hands-on practical examples and a tutorial for solving object detection problems using Python.

Название: Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python
Автор: Sоfiеn Кааbаr
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 350
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Deep Learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on Machine Learning and reinforcement learning. Sofien Kaabar—financial author, trading consultant, and institutional market strategist—introduces Deep Learning strategies that combine technical and quantitative analyses. By fusing Deep Learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. Deep Learning is a slightly more complex and more detailed field than Machine Learning. Machine Learning and Deep Learning both fall under the umbrella of Data Science. As you will see, Deep Learning is mostly about neural networks, a highly sophisticated and powerful algorithm that has enjoyed a lot of coverage and hype, and for good reason: it is very powerful and able to catch highly complex nonlinear relationships between different variables. The book assumes you have basic background knowledge in both Python programming (professional Python users will find the code very straightforward) and financial trading. I take a clear and simple approach that focuses on the key concepts so that you understand the purpose of every idea.

Название: Ultimate Parallel and Distributed Computing with Julia For Data Science: Excel in Data Analysis, Statistical Modeling and Machine Learning by Leveraging MLBase.jl and MLJ.jl to Optimize Workflows
Автор: Nаbаnitа Dаsh
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 484
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Unleash Julia’s power: Code Your Data Stories, Shape Machine Intelligence! This book takes you through a step-by-step learning journey, starting with the essentials of Julia's syntax, variables, and functions. You'll unlock the power of efficient data handling by leveraging Julia arrays and DataFrames.jl for insightful analysis. Develop expertise in both basic and advanced statistical models, providing a robust toolkit for deriving meaningful data-driven insights. The journey continues with Machine Learning proficiency, where you'll implement algorithms confidently using MLJ.jl and MLBase.jl, paving the way for advanced data-driven solutions. Explore the realm of Bayesian inference skills through practical applications using Turing.jl, enhancing your ability to extract valuable insights. The book also introduces crucial Julia packages such as Plots.jl for visualizing data and results. The handbook culminates in optimizing workflows with Julia's parallel and distributed computing capabilities, ensuring efficient and scalable data processing using Distributions.jl, Distributed.jl and SharedArrays.jl. This comprehensive guide equips you with the knowledge and practical insights needed to excel in the dynamic field of Data Science and Machine Learning. In this book, we embark on a journey that explores the powerful intersection of Julia, a high-performance programming language, and the transformative fields of machine learning and data analysis. As technology continues to evolve, the ability to harness and interpret vast amounts of data becomes increasingly crucial. Julia, with its speed, simplicity, and expressive syntax, emerges as an ideal language for tackling the challenges posed by the ever-growing datasets and complex algorithms in these domains.

Название: Epic Python Coding: Interactive Coding Adventures for Kids
Автор: Мikе Gоld
Издательство: Leanpub
Год: 2024-01-02
Страниц: 94
Язык: английский
Формат: pdf (true), epub
Размер: 37.7 MB

Dive into Epic Python Coding! This fun, easy-to-follow guide introduces kids to Python coding. From basic concepts to creating their own game, it's the perfect start for young tech adventurers. Spark creativity and problem-solving skills in the exciting world of programming! Embark on an amazing coding adventure with Epic Python Coding – the perfect guide for kids eager to start their journey into the world of programming. Tailored for 4th graders and up, this book simplifies Python into fun, bite-sized lessons that spark creativity and critical thinking. This book isn't just for young coders; it’s a resource for you too. With a dedicated guide, you can support your kids or students as they learn and grow in their coding skills. Test your new skills with additional exercises and mini-projects. There's always more to learn and explore! Epic Python Coding isn't just a book; it's a doorway to imagination, problem-solving, and a foundational skill that could shape your child's future. Start this exciting journey today and watch young minds turn into tomorrow's tech wizards!

Название: AI Mastery Trilogy: A Comprehensive Guide to AI Basics for Managers, Essential Mathematics for AI, and Coding Practices for Modern Programmers in the AI Era (3-in-1 Collection)(AI Fundamentals)
Автор: Аndrеw Нintоn
Издательство: Book Bound Studios
Год: 2024
Страниц: 436
Язык: английский
Формат: pdf, epub (true)
Размер: 10.8 MB

Dive into the "AI Mastery Trilogy," the ultimate collection for professionals seeking to conquer the world of artificial intelligence (AI). This 3-in-1 compendium is meticulously crafted to guide you from the foundational principles of AI to the intricate mathematical frameworks and practical coding applications that will catapult your expertise to new heights. Book 1: "AI Basics for Managers" by Andrew Hinton is your gateway to understanding and implementing AI in business. It equips managers with the knowledge to navigate the AI landscape, identify opportunities, and lead their organizations toward a future of innovation and growth. Book 2: "Essential Math for AI" demystifies the mathematical backbone of AI, offering a deep dive into the core concepts that fuel AI systems. From linear algebra to game theory, this book is a treasure trove for anyone eager to grasp the numerical and logical foundations that underpin AI's transformative power. Book 3: "AI and ML for Coders" is the hands-on manual for coders ready to harness AI and Machine Learning in their projects. It provides a comprehensive overview of AI and ML technologies, practical coding advice, and ethical considerations, ensuring you're well-equipped to create cutting-edge, responsible AI applications. The "AI Mastery Trilogy" is more than just a set of books; it's a comprehensive learning journey designed to empower business leaders, mathematicians, and coders alike.