Wydawca: K-i-s-publishing
Mark Fisher, Dr. Mark Fisher
Embedded microcontrollers are at the core of many everyday electronic devices. Electronic automotive systems rely on these devices for engine management, anti-lock brakes, in car entertainment, automatic transmission, active suspension, satellite navigation, etc. The so-called internet of things drives the market for such technology, so much so that embedded cores now represent 90% of all processor’s sold. The ARM Cortex-M4 is one of the most powerful microcontrollers on the market and includes a floating point unit (FPU) which enables it to address applications. The ARM Cortex-M4 Microcontroller Cookbook provides a practical introduction to programming an embedded microcontroller architecture. This book attempts to address this through a series of recipes that develop embedded applications targeting the ARM-Cortex M4 device family. The recipes in this book have all been tested using the Keil MCBSTM32F400 board. This board includes a small graphic LCD touchscreen (320x240 pixels) that can be used to create a variety of 2D gaming applications. These motivate a younger audience and are used throughout the book to illustrate particular hardware peripherals and software concepts.C language is used predominantly throughout but one chapter is devoted to recipes involving assembly language. Programs are mostly written using ARM’s free microcontroller development kit (MDK) but for those looking for open source development environments the book also shows how to configure the ARM-GNU toolchain. Some of the recipes described in the book are the basis for laboratories and assignments undertaken by undergraduates.
Articulate Studio Cookbook. Go from Studio newbie to Studio guru
Robert Kennedy
More and more companies find they need to build their training courses internally. They are turning to tools like Articulate Studio because it is easy to use and doesn't have a steep learning curve. If you are familiar with Microsoft PowerPoint in any way, you should feel right at home with Articulate Studio.Articulate Studio Cookbook will get you ready to add Articulate Studio to your enterprise toolkit. This book gives you detailed yet simple steps to complete your training course. By following the clear steps in each chapter, you will gain an understanding of the software but also be able to complete specific tasks and common activities.The good thing about this book is that you can start anywhere and get the information that you need for a specific activity. Cross-references are provided if there is a skill located elsewhere that you need to complete a task.It can be frustrating to pick up a new piece of software and not know where to begin. With Articulate Studio, there is a whole suite of software to work with. You need to know how to work with Presenter, Engage, Quizmaker and Encoder to make great Articulate courses. Then, you'll need to know how to put them all together in a way that makes a professional looking, cohesive and smooth-flowing course. We'll make it easy to follow step by step until you have a professional course.Articulate Studio Cookbook will help you go from Studio newbie to Studio guru. Dive in and choose your recipe.
Zsolt Nagy
Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law.By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!
Denis Rothman
AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples.This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs).This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing.By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.
Denis Rothman, Nicolas GUET, Jérémie ROTHMAN
Artificial intelligence has the potential to replicate humans in every field. Artificial Intelligence By Example serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies.Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks.You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own.By the end of this book, you will have understood the fundamentals of AI and worked through a number of case studies that will help you develop your business vision.
Artificial Intelligence Engines. A Tutorial Introduction to the Mathematics of Deep Learning
James V Stone
This book is a comprehensive guide to the mathematics behind artificial intelligence engines, taking readers from foundational concepts to advanced applications. It begins with an introduction to artificial neural networks, exploring topics like perceptrons, linear associative networks, and gradient descent. Practical examples accompany each chapter, making complex mathematical principles accessible, even for those with limited prior knowledge.The book's detailed structure covers key algorithms like backpropagation, Hopfield networks, and Boltzmann machines, advancing to deep restricted Boltzmann machines, variational autoencoders, and convolutional neural networks. Modern topics such as generative adversarial networks, reinforcement learning, and capsule networks are explored in depth. Each section connects theory to real-world AI applications, helping readers understand how these techniques are used in practice.Ideal for students, researchers, and AI enthusiasts, the book balances theoretical depth with practical insights. Basic mathematical knowledge or foundation is recommended, allowing readers to fully engage with the content. This book serves as an accessible yet thorough resource for anyone eager to dive deeper into artificial intelligence and machine learning.
Artificial Intelligence. Ethical, social, and security impacts for the present and the future
IT Governance Publishing, Dr. Julie E. Mehan
This book offers an in-depth exploration of Artificial Intelligence (AI), from its origins to the ethical and societal challenges it presents today. It provides a comprehensive understanding of AI’s impact on human interaction, collaboration, privacy, and security. Through analyzing both opportunities and risks, the book emphasizes the ethical concerns surrounding AI, such as bias, privacy violations, and security threats.Chapters explore AI’s transformative role in cybersecurity, misinformation, and human-machine collaboration, highlighting its implications for job markets and human relationships. Real-world examples illustrate how AI can drive progress or cause harm. The ethical dilemmas around AI, including its use in surveillance and decision-making, are thoroughly examined, presenting challenges central to modern technology.Looking ahead, the book offers a forward-thinking perspective on AI’s future, discussing emerging trends and the need for responsible policy-making. It concludes by addressing how society can prepare for AI’s continued growth, offering strategies for navigating the evolving landscape. With practical insights and deep analysis, this book helps readers grasp AI’s profound implications for our future.
Anand Deshpande, Manish Kumar, Albenzo Coletta, Giancarlo...
In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data.With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems.By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems.