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Author: Melodena Stephens Publisher: IAP ISBN: 1648024173 Category : Computers Languages : en Pages : 73
Book Description
There are many myths about Artificial Intelligence (AI) relating to what it is and what it can and cannot do. The people making decisions on AI projects are often not technologically savvy and unable to find easy answers. The spending on and the returns from AI projects are not necessarily straightforward. Part of the reason for this is the lack of understanding of the impact of critical decision criteria. AI touches on many ethical concepts - data privacy, validity, and, more importantly, its potential misuse. AI often replaces human decision-making, as managers do not clearly understand the implications of those choices. This book provides an easy and accessible guide for practitioners without a technological background to understand AI. It guides the reader through the fundamental issues confronting decision-makers. It offers advice on ‘how to ask relevant questions’ using the 15 decision scales. There is currently no comparable book on the market that acts as a pocketbook management reference guide for the AI layman.
Author: Melodena Stephens Publisher: IAP ISBN: 1648024173 Category : Computers Languages : en Pages : 73
Book Description
There are many myths about Artificial Intelligence (AI) relating to what it is and what it can and cannot do. The people making decisions on AI projects are often not technologically savvy and unable to find easy answers. The spending on and the returns from AI projects are not necessarily straightforward. Part of the reason for this is the lack of understanding of the impact of critical decision criteria. AI touches on many ethical concepts - data privacy, validity, and, more importantly, its potential misuse. AI often replaces human decision-making, as managers do not clearly understand the implications of those choices. This book provides an easy and accessible guide for practitioners without a technological background to understand AI. It guides the reader through the fundamental issues confronting decision-makers. It offers advice on ‘how to ask relevant questions’ using the 15 decision scales. There is currently no comparable book on the market that acts as a pocketbook management reference guide for the AI layman.
Author: Melodena Stephens Publisher: IAP ISBN: Category : Education Languages : en Pages : 367
Book Description
As the use of AI becomes more and more ubiquitous in companies around the world, managers charged with taking key decisions require resources to enable them to evaluate new projects effectively. The business case for AI projects is not necessarily clear cut and part of the reason for this is the lack of understanding on key decision criteria. AI touches on many ethical concepts - data privacy, validity and more importantly, its potential misuse. AI is often being used to replace human decision-making and there is often no real understanding of the implications of this. This book provides a detailed primer for practitioners without a deep technological background. It guides the reader through the basic issues and offers advice on ‘how to take decisions’. There is a dearth of such books currently available and this book aspires to fill a growing niche. ENDORSEMENTS: "This book is sure to offer value to business users, students and the general public." — K. Ananth Krishnan, Tata Consultancy Services "I highly recommend this book for the leader seeking an up-to-date review of AI to make strategic investments." — Kes Sampanthar, Innovation, BCG Brighthouse "The specificity of application in case studies and easy to understand definitions and recommendations make this a must read in the ever-growing field of literature around AI." — John C. Havens "The AI Enabled Organization is the perfect tool to embark on a thorough assessment of what AI means for your business." — Arno Fehler, Schmidt Kranz Group, Germany
Author: Pete Warden Publisher: O'Reilly Media ISBN: 1492052019 Category : Computers Languages : en Pages : 504
Book Description
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size
Author: Gary Marcus Publisher: Vintage ISBN: 1524748269 Category : Computers Languages : en Pages : 288
Book Description
Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.
Author: Laurence Moroney Publisher: "O'Reilly Media, Inc." ISBN: 1098101715 Category : Computers Languages : en Pages : 329
Book Description
Chapter 2. Introduction to Computer Vision -- Using Neurons for Vision -- Your First Classifier: Recognizing Clothing Items -- The Data: Fashion MNIST -- A Model Architecture to Parse Fashion MNIST -- Coding the Fashion MNIST Model -- Transfer Learning for Computer Vision -- Summary -- Chapter 3. Introduction to ML Kit -- Building a Face Detection App on Android -- Step 1: Create the App with Android Studio -- Step 2: Add and Configure ML Kit -- Step 3: Define the User Interface -- Step 4: Add the Images as Assets -- Step 5: Load the UI with a Default Picture.
Author: C. Venkatesh Publisher: John Wiley & Sons ISBN: 1119762049 Category : Computers Languages : en Pages : 311
Book Description
SMART SYSTEMS FOR INDUSTRIAL APPLICATIONS The prime objective of this book is to provide an insight into the role and advancements of artificial intelligence in electrical systems and future challenges. The book covers a broad range of topics about AI from a multidisciplinary point of view, starting with its history and continuing on to theories about artificial vs. human intelligence, concepts, and regulations concerning AI, human-machine distribution of power and control, delegation of decisions, the social and economic impact of AI, etc. The prominent role that AI plays in society by connecting people through technologies is highlighted in this book. It also covers key aspects of various AI applications in electrical systems in order to enable growth in electrical engineering. The impact that AI has on social and economic factors is also examined from various perspectives. Moreover, many intriguing aspects of AI techniques in different domains are covered such as e-learning, healthcare, smart grid, virtual assistance, etc. Audience The book will be of interest to researchers and postgraduate students in artificial intelligence, electrical and electronic engineering, as well as those engineers working in the application areas such as healthcare, energy systems, education, and others.
Author: Donald J. Norris Publisher: Apress ISBN: 1484227433 Category : Computers Languages : en Pages : 379
Book Description
Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more! AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book. What You'll Learn What AI is and—as importantly—what it is not Inference and expert systems Machine learning both shallow and deep Fuzzy logic and how to apply to an actual control system When AI might be appropriate to include in a system Constraints and limitations of the Raspberry Pi AI implementation Who This Book Is For Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.
Author: Dr. Joshua Eckroth Publisher: Packt Publishing Ltd ISBN: 1789538246 Category : Computers Languages : en Pages : 155
Book Description
Build smart applications by implementing real-world artificial intelligence projects Key Features Explore a variety of AI projects with Python Get well-versed with different types of neural networks and popular deep learning algorithms Leverage popular Python deep learning libraries for your AI projects Book Description Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence. This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library. By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress What you will learn Build a prediction model using decision trees and random forest Use neural networks, decision trees, and random forests for classification Detect YouTube comment spam with a bag-of-words and random forests Identify handwritten mathematical symbols with convolutional neural networks Revise the bird species identifier to use images Learn to detect positive and negative sentiment in user reviews Who this book is for Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you’re able to play around with code
Author: Melodena Stephens
Author: Melodena Stephens
Author: Melodena Stephens
Author: Pete Warden
Author: Gary Marcus
Author: George Jean Nathan
Author: 
Author: Laurence Moroney
Author: C. Venkatesh
Author: Donald J. Norris
Author: Dr. Joshua Eckroth