Take a look at our Artificial Intelligence books. Shulph carries a great selection of Artificial Intelligence books, and we are always adding more.
The essential blueprints and workflow you need to build successful AI business applications Key Features Learn and master the essential blueprints to program AI for real-world business applications Gain insights into how modern AI and machine learning solve core business challenges Acquire practical techniques and a workflow that can build AI applications using state-of-the-art software libraries Work with a practical, code-based strategy for creating successful AI solutions in your business Book Description AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You'll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you'll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You'll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a 'trending now' section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers' questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you'll also learn how to prepare for future advances in AI. You'll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. What you will learn An essential toolbox of blueprints and advanced techniques for building AI business applications How to design and deploy AI applications that meet today's business needs A workflow from first design stages to practical code solutions in your next AI projects Solutions for AI projects that involve social media analytics and recommendation engines Practical projects and techniques for sentiment analysis and helpful chatbots A blueprint for AI projects that recommend products based on customer purchasing habits How to prepare yourself for the next decade of AI and machine learning advancements Who this book is for Programming AI Business Applications provides an introduction to AI with real-world examples. This book can be read and understood by programmers and students without requiring previous AI experience. The projects in this book make use of Java and Python and several popular and state-of-the-art opensource AI libraries.
This friendly and accessible guide to AI theory and programming in Python requires no maths or data science background. Key Features - Roll up your sleeves and start programming AI models - No math, data science, or machine learning background required - Packed with hands-on examples, illustrations, and clear step-by-step instructions - 5 hands-on working projects put ideas into action and show step-by-step how to build intelligent software Book Description AI is changing the world – and with this book, anyone can start building intelligent software. Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Taking a graduated approach that starts with the basics before easing readers into more complicated formulas and notation, Hadelin helps you understand what you really need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming: - Google Colab - Python - TensorFlow - Keras - PyTorch AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learn - Master the key skills of deep learning, reinforcement learning, and deep reinforcement learning - Understand Q-learning and deep Q-learning - Learn from friendly, plain English explanations and practical activities - Build fun projects, including a virtual-self-driving car - Use AI to solve real-world business problems and win classic video games - Build an intelligent, virtual robot warehouse worker Who this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
Artificial Intelligence and Global Security: Future Trends, Threats and Considerations brings a much-needed perspective on the impact of the integration of artificial intelligence (AI) technologies in military affairs. Experts forecast that AI will shape future military operations in ways that will revolutionize warfare. That is why there is an urgent need to consider the potential ethical and moral consequences related to enabling AI to make decisions that will shape the future world. This book masterfully presents a vision of a future that is replete with integrated networks of artificial intelligence that are designed to both defend and attack nations. Artificial Intelligence and Global Security: Future Trends, Threats and Considerations has rendered a major service to those interested in the impact of artificial intelligence technologies and its contribution to the evolution and revolution in military warfare. It also explores the implications of AI for the individual, for personal identity, for society, and for global security; it examines the impact of AI on Just War Theory; and it offers diverse perspectives on the consequences of the integration of AI in our daily lives and society.
Create AI applications in Python and lay the foundations for your career in data science Key Features - Practical examples that explain key machine learning algorithms - Explore neural networks in detail with interesting examples - Master core AI concepts with engaging activities Book Description 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! What you will learn - Understand the importance, principles, and fields of AI - Implement basic artificial intelligence concepts with Python - Apply regression and classification concepts to real-world problems - Perform predictive analysis using decision trees and random forests - Carry out clustering using the k-means and mean shift algorithms - Understand the fundamentals of deep learning via practical examples Who this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it's recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
HR professionals need to get to grips with artificial intelligence and the way it's changing the world of work. From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chatbots to enhance the employee experience, AI has created a variety of opportunities for the HR function. Artificial Intelligence for HR empowers HR professionals to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR in practice. Covering everything from recruitment and retention to employee engagement and learning and development, Artificial Intelligence for HR outlines the value AI can add to HR. It also features discussions on the challenges that can arise from AI and how to deal with them, including data privacy, algorithmic bias and how to develop the skills of a workforce with the rise of automation, robotics and machine learning in order to make it more human, not less. Packed with practical advice, research and case studies from global organizations including Uber, IBM and Unilever, this book will equip HR professionals with the knowledge they need to leverage AI to recruit and develop a successful workforce and help their businesses thrive in the future.
Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book Description Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence. What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot's intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics.
The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field. Online resources: bonus chapters on AI, ensembles and neural nets, and finishing experiments, plus single and multiple product simulators.
Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features Study ROS, the main development framework for robotics, in detail Learn all about convolutional neural networks, recurrent neural networks, and robotics Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn Explore the ROS and build a basic robotic system Understand the architecture of neural networks Identify conversation intents with NLP techniques Learn and use the embedding with Word2Vec and GloVe Build a basic CNN and improve it using generative models Use deep learning to implement artificial intelligence(AI)and object recognition Develop a simple object recognition system using CNNs Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.
Cyber Minds brings together an unrivalled panel of international experts who offer their insights into current cybersecurity issues in the military, business, and government. Key Features - Explore the latest developments in cybersecurity - Hear expert insight from the industry's top practitioners - Dive deep into cyber threats in business, government, and military Book Description Shira Rubinoff's Cyber Minds brings together the top authorities in cybersecurity to discuss the emergent threats that face industries, societies, militaries, and governments today. With new technology threats, rising international tensions, and state-sponsored cyber attacks, cybersecurity is more important than ever. Cyber Minds serves as a strategic briefing on cybersecurity and data safety, collecting expert insights from sector security leaders, including: - General Gregory Touhill, former Federal Chief Information Security Officer of the United States - Kevin L. Jackson, CEO and Founder, GovCloud - Mark Lynd, Digital Business Leader, NETSYNC - Joseph Steinberg, Internet Security advisor and thought leader - Jim Reavis, Co-Founder and CEO, Cloud Security Alliance - Dr. Tom Kellerman, Chief Cybersecurity Officer for Carbon Black Inc and Vice Chair of Strategic Cyber Ventures Board - Mary Ann Davidson, Chief Security Officer, Oracle - Dr. Sally Eaves, Emergent Technology CTO, Global Strategy Advisor – Blockchain AI FinTech, Social Impact award winner, keynote speaker and author - Dr. Guenther Dobrauz, Partner with PwC in Zurich and Leader of PwC Legal Switzerland - Barmak Meftah, President, AT&T Cybersecurity - Cleve Adams, CEO, Site 1001 (AI and big data based smart building company) - Ann Johnson, Corporate Vice President – Cybersecurity Solutions Group, Microsoft - Barbara Humpton, CEO, Siemens USA Businesses and states depend on effective cybersecurity. This book will help you to arm and inform yourself on what you need to know to keep your business – or your country – safe. What you will learn - The threats and opportunities presented by AI - How to mitigate social engineering and other human threats - Developing cybersecurity strategies for the cloud - Major data breaches, their causes, consequences, and key takeaways - Blockchain applications for cybersecurity - Implications of IoT and how to secure IoT services - The role of security in cyberterrorism and state-sponsored cyber attacks Who this book is for: This book is essential reading for business leaders, the C-Suite, board members, IT decision makers within an organization, and anyone with a responsibility for cybersecurity.
Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease Key Features Enter the world of AI with the help of solid concepts and real-world use cases Explore AI components to build real-world automated intelligence Become well versed with machine learning and deep learning concepts Book Description Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world. Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games. By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications. What you will learn Use TensorFlow packages to create AI systems Build feedforward, convolutional, and recurrent neural networks Implement generative models for text generation Build reinforcement learning algorithms to play games Assemble RNNs, CNNs, and decoders to create an intelligent assistant Utilize RNNs to predict stock market behavior Create and scale training pipelines and deployment architectures for AI systems Who this book is for This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.