Название: DNAI: The AI Management (AIM) Framework Автор: Каrtik Sаkthivеl Издательство: Brain Fuel Books, LLC Год: 2024 Страниц: 418 Язык: английский Формат: pdf Размер: 51.7 MB Artificial Intelligence (AI) is transforming our world at a pace that has never been seen before. A seminal moment for our species, AI will reshape and recreate entire industries and professions. Sustained success with AI isn’t just about AI adoption - to harness AI’s full potential, incorporating best practices into the very DNA of your organization is of paramount importance. Whether you're in a business role or an IT role, an executive, a seasoned professional, or just stepping into AI, this book equips you with the insights, strategies, and frameworks to embed AI into your organization's DNA for sustained success. This book introduces the Artificial Intelligence Management (AIM) Framework - 25 best practices and 4 basic principles - including turnkey, customizable, and extensible tools that can be applied within your organizations. Apply the AIM Framework to be able to capitalize on the promise of AI and avoiding potential pitfalls. Actioned in unison with your own corporate goals, the AIM Framework is a vital prescriptive instrument for you to engineer splicing AI into the strands of your corporate DNA to equip yourself and your firms to realize sustained and long-term success with AI.
Название: Python for Artificial Intelligence: A Comprehensive Guide Автор: Неshаm Моhаmеd Еlshеrif Издательство: Eldonusa Publishing Год: 2024 Страниц: 247 Язык: английский Формат: pdf Размер: 23.9 MB Welcome to "Python for Artificial Intelligence: A Comprehensive Guide." In today's rapidly evolving technological landscape, Artificial Intelligence (AI) stands at the forefront of innovation, driving transformative changes across industries and domains. At the heart of AI lies Python, a versatile and powerful programming language renowned for its simplicity, flexibility, and rich ecosystem of libraries and frameworks. This book is crafted as a comprehensive guide to mastering Python for AI, catering to learners of all levels, from aspiring beginners to seasoned practitioners. Whether you're a student, a professional developer, or an AI enthusiast eager to delve into the world of machine learning and deep learning, this book is your roadmap to success. Python boasts a vast ecosystem of libraries and frameworks tailored for AI, including TensorFlow, Keras, PyTorch, scikit-learn, and more. These libraries provide powerful tools and algorithms for building sophisticated AI models with ease.
Название: Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors: Volume 2 Автор: Аtiqur Rаhmаn Аhаd, Sоzо Inоuе, Guillаumе Lореz Издательство: CRC Press Год: 2024 Страниц: 285 Язык: английский Формат: pdf (true) Размер: 18.6 MB Human Activity and Behavior Analysis relates to the field of vision and sensor-based human action or activity and behavior analysis and recognition. The book includes a series of methodologies, surveys, relevant datasets, challenging applications, ideas, and future prospects. Activity recognition has been a hot research topic for some years now. One of its main applications is ambient assisted living, so that people in need of assistance might stay in their own environment longer than previously possible. There is a wide range of sensors of different types and applications being tested in this domain, ranging from ambient binary motion sensors and pressure mats to wearable gyroscopes or sensors monitoring body functions. This is also due to the many different levels of surveillance tested by the researchers. The library we selected to use here is Apache Beam and in-memory database Redis. There are two reasons to use Apache Beam: The first is the ease of implementation. Apache Beam can be written in programming languages such as Java or Python, and the process is represented as a pipeline, so it is intuitive and easy to implement. We used Machine Learning methods for classification and extracted statistical features from raw 3-D acceleration and 3-D angular velocity for each axis within the segment. In this work, we compared three types of classifiers, multi-class support vector machine (SVM), Random Forest (RF), and K Nearest Neighbors (KNN) from Scikit-learn, a Machine Learning library for Python. We chose to set all of the parameters of Machine Learning models to default values of Scikit-learn. Before training data with classifiers, we chose RF and KNN classifiers which calculate distances between different points in their algorithm.
Название: Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors: Volume 1 Автор: Аtiqur Rаhmаn Аhаd, Sоzо Inоuе, Guillаumе Lореz Издательство: CRC Press Год: 2024 Страниц: 457 Язык: английский Формат: pdf (true) Размер: 21.9 MB The book discusses topics such as action recognition, action understanding, gait analysis, gesture recognition, behavior analysis, emotion and affective computing, and related areas. Sensors and cameras are exploited for the analysis and recognition of human activity and behavior. In the book Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors, we have divided across two volumes, 40 wonderful chapters under five parts: Part 1: Healthcare and Emotion (Chapters 1–7), Part 2: Mental Health (Chapters 8–14), Part 3: Nurse Care Records (Chapters 15–26), Part 4: Movement and Sensors (Chapters 27–36), and Part 5: Sports Activity Analysis (Chapters 37–40). In a complex problem such as stress detection, the application of some type of Machine Learning (ML) algorithms makes sense. The vast amount of data in a context where multiple variables, such as HR, HRV, GSR, and ST, might have different outputs based on each other, makes it a prime target for the ML approach. Some of the most common classification algorithms are Support Vector Machines (SVM), K-Nearest Neighbours (K-NN), Random Forests (RF), Decision Trees, and Naive Bayes (NB). The data processing and model development used different Python libraries such as Pandas, Tensorflow, and Keras. To recognize stress from the physiological data, we tested different Machine Learning algorithms. We implemented the approach using Python and the Scikit-learn library.
Название: The Secrets of AI Value Creation: A Practical Guide to Business Value Creation with Artificial Intelligence from Strategy to Execution Автор: Мiсhаеl Рrоksсh, Nishа Раliwаl, Wilhеlm Вiеlеrt Издательство: Wiley Год: 2024 Страниц: 416 Язык: английский Формат: epub (true) Размер: 10.1 MB Unlock unprecedented levels of value at your firm by implementing Artificial Intelligence (AI). In The Secrets of AI Value Creation: Practical Guide to Business Value Creation with Artificial Intelligence from Strategy to Execution, a team of renowned artificial intelligence leaders and experts delivers an insightful blueprint for unlocking the value of AI in your company. This book presents a comprehensive framework that can be applied to your organisation, exploring the value drivers and challenges you might face throughout your AI journey. You will uncover effective strategies and tactics utilised by successful Artificial Intelligence (AI) achievers to propel business growth. In the book, you'll explore critical value drivers and key capabilities that will determine the success or failure of your company's AI initiatives. The authors examine the subject from multiple perspectives, including business, technology, data, algorithmics, and psychology. Whether you're just someone interested in exploring the subject or a seasoned business leader, an AI expert, an enterprise data and AI manager, a data scientist, an engineer, or an AI start‐up, you might be seeking guidance on how to create value with AI. Regardless of your background, you may find yourself wrestling with the puzzle of AI's value creation.
Название: Computer Science in Sport: Modeling, Simulation, Data Analysis and Visualization of Sports-Related Data Автор: Dаniеl Меmmеrt Издательство: Springer Год: 2024 Страниц: 247 Язык: английский Формат: pdf (true), epub Размер: 17.7 MB In recent years, computer science in sport has grown extremely, mainly because more and more new data has become available. Computer Science tools in sports, whether used for opponent preparation, competition, or scientific analysis, have become indispensable across various levels of expertise nowadays. A completely new market has emerged through the utilization of these tools in the four major fields of application: clubs and associations, business, science, and the media. This market is progressively gaining importance within university research and educational activities. This textbook aims to live up to the now broad diversity of Computer Science in sport by having more than 30 authors report from their special field and concisely summarise the latest findings. The book is divided into four main sections: data sets, modelling, simulation and data analysis. In addition to background information on programming languages (R and Python) and visualisation, the textbook is framed by history and an outlook. Python is highly popular in the community of data scientists in general and sports analysts in particular because it is a open-source, dynamic, object-oriented, high-level programming language, which provides highly flexible and up-to-date functionalities due to its available modules and libraries.
Название: Security Strategies in Windows Platforms and Applications, 4th Edition Автор: Rоbеrt Shimоnski, Мiсhаеl G. Sоlоmоn Издательство: Jones & Bartlett Learning Год: 2024 Страниц: 904 Язык: английский Формат: epub Размер: 22.8 MB Revised and updated to keep pace with this ever-changing field, Security Strategies in Windows Platforms and Applications, Fourth Edition focuses on new risks, threats, and vulnerabilities associated with the Microsoft Windows operating system, placing a particular emphasis on Windows 11, and Windows Server 2022. The Fourth Edition highlights how to use tools and techniques to decrease risks arising from vulnerabilities in Microsoft Windows operating systems and applications. The book also includes a resource for readers desiring more information on Microsoft Windows OS hardening, application security, and incident management. With its accessible writing style, and step-by-step examples, this must-have resource will ensure readers are educated on the latest Windows security strategies and techniques. This book has also been fully updated to reflect current technology trends such as cloud, AI/ML, DevOps and the use of Microsoft Azure.
Название: Effective Machine Learning Teams: Best Practices for Ml Practitioners (Final) Автор: Dаvid Таn, Аdа Lеung, Dаvid Соlls Издательство: O’Reilly Media, Inc. Год: 2024 Страниц: 402 Язык: английский Формат: pdf (true), epub (true) Размер: 15.1 MB, 10.1 MB Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to apply time-tested software engineering skills and Lean product delivery practices to reduce toil and waste, shorten feedback loops, and improve your team's flow when building ML systems and products. Based on the authors' experience across multiple real-world data and ML projects, the proven techniques in this book will help your team avoid common traps in the ML world, so you can iterate and scale more quickly and reliably. You'll learn how to overcome friction and experience flow when delivering ML solutions.
Название: GoLang for Machine Learning: A Hands-on-Guide to Building Efficient, Smart and Scalable ML Models with Go Programming Автор: Еvаn Аtkins Издательство: Independently published Год: 2024 Страниц: 155 Язык: английский Формат: pdf Размер: 19.1 MB Go, the high-performance language from Google, is rapidly gaining traction in the Machine Learning (ML) world. Its speed, concurrency, and built-in features make it ideal for building efficient, scalable ML models. But where do you start? This book is written by a seasoned developer and Machine Learning expert, providing you with practical, hands-on guidance based on real-world experience. After reading this book, you'll be equipped with the knowledge and tools to create robust, performant models without sacrificing clarity or maintainability. Hands-on projects covering various Machine Learning tasks, from regression and classification to image recognition and natural language processing. This book is designed for programmers with some coding experience who are interested in applying Go to Machine Learning. Whether you're a data scientist, software engineer, or simply curious about Go's potential, this guide will empower you to create impactful ML models. Stop struggling with slow, complex ML frameworks. Start building efficient, scalable models with Go. Get your copy of GoLang for Machine Learning today and embark on your journey to smarter, faster AI!
Название: Adversarial Multimedia Forensics Автор: Еhsаn Nоwrооzi, Каssеm Каllаs, Аlirеzа Jоlfаеi Издательство: Springer Серия: Advances in Information Security Год: 2024 Страниц: 298 Язык: английский Формат: pdf (true), epub Размер: 45.9 MB This book explores various aspects of digital forensics, security and Machine Learning, while offering valuable insights into the ever-evolving landscape of multimedia forensics and data security. This book’s content can be summarized in two main areas. The first area of this book primarily addresses techniques and methodologies related to digital image forensics. It discusses advanced techniques for image manipulation detection, including the use of Deep Learning architectures to generate and manipulate synthetic satellite images. This book also explores methods for face recognition under adverse conditions and the importance of forensics in criminal investigations. Additionally, the book highlights anti-forensic measures applied to photos and videos, focusing on their effectiveness and trade-offs. Intended for those in Computer Science, engineering, and other related fields, this book explores the challenges and opportunities of the adversarial side of multimedia forensics. Some Machine Learning and signal processing basics are helpful but are not required. The goal is to equip readers with the knowledge to navigate this complex space and drive innovation in this exciting, ever-changing field.
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