Artificial Intelligence

Artificial Intelligence PDF Author: Neil Wilkins
Publisher: Independently Published
ISBN: 9781092879675
Category :
Languages : en
Pages : 214

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Book Description
If you want to learn key AI concepts to get you quickly up to speed with all things AI, then keep reading Two manuscripts in one book: Artificial Intelligence: What You Need to Know About Machine Learning, Robotics, Deep Learning, Recommender Systems, Internet of Things, Neural Networks, Reinforcement Learning, and Our Future Internet of Things: What You Need to Know About IoT, Big Data, Predictive Analytics, Artificial Intelligence, Machine Learning, Cybersecurity, Business Intelligence, Augmented Reality and Our Future This book covers everything from machine learning to robotics and the internet of things. You can use it as a nifty guidebook whenever you come across news headlines that talk about some new advancement in AI by Google or Facebook. By the time you finish reading, you will be aware of what artificial neural networks are, how gradient descent and back propagation work, and what deep learning is. You will also learn a comprehensive history of AI, from the first invention of automations in antiquity to the driver-less cars of today. In part 1 of this book, you will: Understand how machines can "think" and how they learn Learn the five reasons why experts are warning us about AI research Find the answers to the top six myths of artificial intelligence Learn what neural networks are and how they work, the "brains" of machine learning Understand reinforcement learning and how it is used to teach machine learning systems through experience Become up-to-date with the current state-of-the-art artificial intelligence methods that use deep learning Learn the basics of recommender systems Expand your current view of machines and what is possible with modern robotics Enter the vast world of the internet of things technologies Find out why AI is the new business degree And much, much more! Some of the topics covered in part 2 of this book include: Origins of IoT IoT Security Ethical Hacking Internet of Things Under The Cushy Foot of Tech Giants The Power of Infinite Funds IoT Toys Bio-robotics Predictive Analytics Machine Learning Artificial Intelligence Cybersecurity Big Data Business Intelligence Augmented Reality Virtual Reality Our Future And much, much more If you want to learn more about the artificial intelligence and internet of things, then scroll up and click "add to cart"!

Artificial Intelligence

Artificial Intelligence PDF Author: Neil Wilkins
Publisher: Independently Published
ISBN: 9781092879675
Category :
Languages : en
Pages : 214

Get Book Here

Book Description
If you want to learn key AI concepts to get you quickly up to speed with all things AI, then keep reading Two manuscripts in one book: Artificial Intelligence: What You Need to Know About Machine Learning, Robotics, Deep Learning, Recommender Systems, Internet of Things, Neural Networks, Reinforcement Learning, and Our Future Internet of Things: What You Need to Know About IoT, Big Data, Predictive Analytics, Artificial Intelligence, Machine Learning, Cybersecurity, Business Intelligence, Augmented Reality and Our Future This book covers everything from machine learning to robotics and the internet of things. You can use it as a nifty guidebook whenever you come across news headlines that talk about some new advancement in AI by Google or Facebook. By the time you finish reading, you will be aware of what artificial neural networks are, how gradient descent and back propagation work, and what deep learning is. You will also learn a comprehensive history of AI, from the first invention of automations in antiquity to the driver-less cars of today. In part 1 of this book, you will: Understand how machines can "think" and how they learn Learn the five reasons why experts are warning us about AI research Find the answers to the top six myths of artificial intelligence Learn what neural networks are and how they work, the "brains" of machine learning Understand reinforcement learning and how it is used to teach machine learning systems through experience Become up-to-date with the current state-of-the-art artificial intelligence methods that use deep learning Learn the basics of recommender systems Expand your current view of machines and what is possible with modern robotics Enter the vast world of the internet of things technologies Find out why AI is the new business degree And much, much more! Some of the topics covered in part 2 of this book include: Origins of IoT IoT Security Ethical Hacking Internet of Things Under The Cushy Foot of Tech Giants The Power of Infinite Funds IoT Toys Bio-robotics Predictive Analytics Machine Learning Artificial Intelligence Cybersecurity Big Data Business Intelligence Augmented Reality Virtual Reality Our Future And much, much more If you want to learn more about the artificial intelligence and internet of things, then scroll up and click "add to cart"!

AI for People and Business

AI for People and Business PDF Author: Alex Castrounis
Publisher: O'Reilly Media
ISBN: 1492036544
Category : Computers
Languages : en
Pages : 317

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Book Description
If you’re an executive, manager, or anyone interested in leveraging AI within your organization, this is your guide. You’ll understand exactly what AI is, learn how to identify AI opportunities, and develop and execute a successful AI vision and strategy. Alex Castrounis, business consultant and former IndyCar engineer and race strategist, examines the value of AI and shows you how to develop an AI vision and strategy that benefits both people and business. AI is exciting, powerful, and game changing—but too many AI initiatives end in failure. With this book, you’ll explore the risks, considerations, trade-offs, and constraints for pursuing an AI initiative. You’ll learn how to create better human experiences and greater business success through winning AI solutions and human-centered products. Use the book’s AIPB Framework to conduct end-to-end, goal-driven innovation and value creation with AI Define a goal-aligned AI vision and strategy for stakeholders, including businesses, customers, and users Leverage AI successfully by focusing on concepts such as scientific innovation and AI readiness and maturity Understand the importance of executive leadership for pursuing AI initiatives "A must read for business executives and managers interested in learning about AI and unlocking its benefits. Alex Castrounis has simplified complex topics so that anyone can begin to leverage AI within their organization." - Dan Park, GM & Director, Uber "Alex Castrounis has been at the forefront of helping organizations understand the promise of AI and leverage its benefits, while avoiding the many pitfalls that can derail success. In this essential book, he shares his expertise with the rest of us." - Dean Wampler, Ph.D., VP, Fast Data Engineering at Lightbend

AI and Machine Learning for Coders

AI and Machine Learning for Coders PDF Author: Laurence Moroney
Publisher: O'Reilly Media
ISBN: 1492078166
Category : Computers
Languages : en
Pages : 393

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Book Description
If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving

The Executive Guide to Artificial Intelligence

The Executive Guide to Artificial Intelligence PDF Author: Andrew Burgess
Publisher: Springer
ISBN: 3319638203
Category : Business & Economics
Languages : en
Pages : 187

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Book Description
This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.

Grokking Deep Learning

Grokking Deep Learning PDF Author: Andrew W. Trask
Publisher: Simon and Schuster
ISBN: 163835720X
Category : Computers
Languages : en
Pages : 475

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Book Description
Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch PDF Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624

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Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Learn Python From an Expert: The Complete Guide: With Artificial Intelligence

Learn Python From an Expert: The Complete Guide: With Artificial Intelligence PDF Author: Edson L P Camacho
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 620

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Book Description
The Ultimate Guide to Advanced Python and Artificial Intelligence: Unleash the Power of Code! Are you ready to take your Python programming skills to the next level and dive into the exciting world of artificial intelligence? Look no further! We proudly present the comprehensive book written by renowned author Edson L P Camacho: "Advanced Python: Mastering AI." In today's rapidly evolving technological landscape, the demand for AI professionals is soaring. Python, with its simplicity and versatility, has become the go-to language for AI development. Whether you are a seasoned Pythonista or a beginner eager to learn, this book is your gateway to mastering AI concepts and enhancing your programming expertise. What sets "Advanced Python: Mastering AI" apart from other books is its unparalleled combination of in-depth theory and hands-on practicality. Edson L P Camacho, a leading expert in the field, guides you through every step, from laying the foundation of Python fundamentals to implementing cutting-edge AI algorithms. Here's a glimpse of what you'll find within the pages of this comprehensive guide: 1. Python Fundamentals: Review and reinforce your knowledge of Python basics, including data types, control flow, functions, and object-oriented programming. Build a solid foundation to tackle complex AI concepts. 2. Data Manipulation and Visualization: Learn powerful libraries such as NumPy, Pandas, and Matplotlib to handle and analyze data. Understand how to preprocess and visualize data effectively for AI applications. 3. Machine Learning Essentials: Dive into the world of machine learning and explore popular algorithms like linear regression, decision trees, support vector machines, and neural networks. Discover how to train, evaluate, and optimize models for various tasks. 4. Deep Learning and Neural Networks: Delve deeper into neural networks, the backbone of modern AI. Gain insights into deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Implement advanced techniques like transfer learning and generative models. 5. Natural Language Processing (NLP): Explore the fascinating field of NLP and learn how to process and analyze textual data using Python. Discover techniques like sentiment analysis, named entity recognition, and text generation. 6. Computer Vision: Unleash the power of Python for image and video analysis. Build computer vision applications using popular libraries like OpenCV and TensorFlow. Understand concepts like object detection, image segmentation, and image captioning. 7. Reinforcement Learning: Embark on the exciting journey of reinforcement learning. Master the fundamentals of Q-learning, policy gradients, and deep Q-networks. Create intelligent agents that can learn and make decisions in dynamic environments. "Advanced Python: Mastering AI" not only equips you with the theoretical knowledge but also provides numerous real-world examples and projects to reinforce your understanding. Each chapter is accompanied by practical exercises and coding challenges to sharpen your skills and boost your confidence. Don't miss the opportunity to stay ahead in this AI-driven era. Order your copy of "Advanced Python: Mastering AI" today and unlock the full potential of Python programming with artificial intelligence. Take your career to new heights and become a proficient AI developer. Get ready to write the code that shapes the future!

Competing in the Age of AI

Competing in the Age of AI PDF Author: Marco Iansiti
Publisher: Harvard Business Press
ISBN: 1633697630
Category : Business & Economics
Languages : en
Pages : 175

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Book Description
"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.

Deep Learning Illustrated

Deep Learning Illustrated PDF Author: Jon Krohn
Publisher: Addison-Wesley Professional
ISBN: 0135121728
Category : Computers
Languages : en
Pages : 725

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Book Description
"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Trustworthy AI

Trustworthy AI PDF Author: Beena Ammanath
Publisher: John Wiley & Sons
ISBN: 1119867959
Category : Computers
Languages : en
Pages : 230

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Book Description
An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.