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Author: Diego Gosmar
Publisher:
ISBN:
Category :
Languages : en
Pages : 258
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Book Description
★ COLOR VERSION ★ New edition updated 2021! Machine learning is one of the most powerful artificial intelligence techniques, capable of efficiently managing and analyzing large amounts of data, to provide accurate predictions, automated decisions and deliver unprecedented business benefits. This volume aims to illustrate in the simplest possible way which are the main approaches in the Machine Learning universe, as well as providing some examples of real applications from which the reader can draw inspiration to understand the benefits and design applications of common interest. Among the covered topics you will find: * Practical applications: regression and classification predictions * Sentiment analysis * Speech Analytics * Image recognition * Performance analysis * Numerous examples and graphical displays of the results * Wavelet Transform for AI non-stationary signal processing * Supervised, Unsupervised and Reinforcement Learning * Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks * AutoML * MLOps and Pipeline for Distributed Architectures to improve Governance and Scalability The author describes the essential principles and methods of ML (Machine Learning) clearly, making the book suitable even for non-IT readers or data scientists who are experts in the field. Business innovation managers and departments can also benefit from reading this book to better understand how ML can streamline its operations and increase productivity, with an eye to the future. After a first introduction to the concepts of data science and the nomenclature often adopted when it comes to Machine Learning, the book offers a description of the three main methodologies adopted today, trying to analyze both the benefits and the critical issues. Some of the most common learning models are illustrated and the various steps for preparing the data are then analyzed together with the training, testing and accuracy assessment phases. Some of the IT tools that can be used to work on Machine Learning are then described (with emphasis on Open Source ones). The second part of the book deals with different techniques of Regression, Classification and Deep Learning, as well as the methodologies to optimize the results and combine the adopted algorithms. We examine the subject of model interpretability and also of AI security, to move on to an overview of visualization and analysis techniques during Machine Learning processes. The final part focuses on real applications. Two practical cases related to real business applications are dealt with, the approaches to face them, the tools adopted are described and all the source code is made available, commenting it step by step for greater understanding. This volume tries to deal with concepts related to the world of Machine Learning using a language suitable for a wider audience possible, because Machine Learning is part of the fascinating vast world of data science, which brings together various skills: technology, analysis and business understanding.
Author: Diego Gosmar
Publisher:
ISBN:
Category :
Languages : en
Pages : 258
Get Book Here
Book Description
★ COLOR VERSION ★ New edition updated 2021! Machine learning is one of the most powerful artificial intelligence techniques, capable of efficiently managing and analyzing large amounts of data, to provide accurate predictions, automated decisions and deliver unprecedented business benefits. This volume aims to illustrate in the simplest possible way which are the main approaches in the Machine Learning universe, as well as providing some examples of real applications from which the reader can draw inspiration to understand the benefits and design applications of common interest. Among the covered topics you will find: * Practical applications: regression and classification predictions * Sentiment analysis * Speech Analytics * Image recognition * Performance analysis * Numerous examples and graphical displays of the results * Wavelet Transform for AI non-stationary signal processing * Supervised, Unsupervised and Reinforcement Learning * Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks * AutoML * MLOps and Pipeline for Distributed Architectures to improve Governance and Scalability The author describes the essential principles and methods of ML (Machine Learning) clearly, making the book suitable even for non-IT readers or data scientists who are experts in the field. Business innovation managers and departments can also benefit from reading this book to better understand how ML can streamline its operations and increase productivity, with an eye to the future. After a first introduction to the concepts of data science and the nomenclature often adopted when it comes to Machine Learning, the book offers a description of the three main methodologies adopted today, trying to analyze both the benefits and the critical issues. Some of the most common learning models are illustrated and the various steps for preparing the data are then analyzed together with the training, testing and accuracy assessment phases. Some of the IT tools that can be used to work on Machine Learning are then described (with emphasis on Open Source ones). The second part of the book deals with different techniques of Regression, Classification and Deep Learning, as well as the methodologies to optimize the results and combine the adopted algorithms. We examine the subject of model interpretability and also of AI security, to move on to an overview of visualization and analysis techniques during Machine Learning processes. The final part focuses on real applications. Two practical cases related to real business applications are dealt with, the approaches to face them, the tools adopted are described and all the source code is made available, commenting it step by step for greater understanding. This volume tries to deal with concepts related to the world of Machine Learning using a language suitable for a wider audience possible, because Machine Learning is part of the fascinating vast world of data science, which brings together various skills: technology, analysis and business understanding.
Author: Arindam Ganguly
Publisher: BPB Publications
ISBN: 9390684706
Category : Computers
Languages : en
Pages : 222
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Book Description
Utilize Python and IBM Watson to put real-life use cases into production. KEY FEATURES ● Use of popular Python packages for building Machine Learning solutions from scratch. ● Practice various IBM Watson Machine Learning tools for Computer Vision and Natural Language Processing applications. ● Expert-led best practices to put your Machine Learning solutions into the production environment. DESCRIPTION This book will take you through the journey of some amazing tools IBM Watson has to offer to leverage your machine learning concepts to solve some real-life use cases that are pertinent to the current industry. This book explores the various Machine Learning fundamental concepts and how to use the Python programming language to deal with real-world use cases. It explains how to take your code and deploy it into IBM Cloud leveraging IBM Watson Machine Learning. While doing so, the book also introduces you to several amazing IBM Watson tools such as Watson Assistant, Watson Discovery, and Watson Visual Recognition to ease out various machine learning tasks such as building a chatbot, creating a natural language processing pipeline, or an optical object detection application without a single line of code. It covers Watson Auto AI with which you can apply various machine learning algorithms and pick out the best for your dataset without a single line of code. Finally, you will be able to deploy all of these into IBM Cloud and configure your application to maintain the production-level runtime. After reading this book, you will find yourself confident to administer any machine learning use case and deploy it into production without any hassle. You will be able to take up a complete end-to-end machine learning project with complete responsibility and deliver the best standards the current industry has to offer. Towards the end of this book, you will be able to build an end-to-end production-level application and deploy it into Cloud. WHAT YOU WILL LEARN ● Review the basics of Machine Learning and learn implementation using Python. ● Learn deployment using IBM Watson Studio and Watson Machine Learning. ● Learn how to use Watson Auto AI to automate hyperparameter tuning. ● Learn Watson Assistant, Watson Visual Recognition, and Watson Discovery. ● Learn how to implement the various layers of an end-to-end AI application. ● Learn all the configurations needed for production deployment to Cloud. WHO THIS BOOK IS FOR This book is for all data professionals, ML enthusiasts, and software developers who are looking for real solutions to be developed. The reader is expected to have a prior knowledge of the web application architecture and basic Python fundamentals. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Deep Learning 3. Features and Metrics 4. Build Your Own Chatbot 5. First Complete Machine Learning Project 6. Perfecting Our Model 7. Visual Recognition 8. Watson Discovery 9. Deployment and Others 10. Deploying the Food Ordering Bot
Author: Joel Stafford
Publisher:
ISBN: 9781690959151
Category :
Languages : en
Pages : 101
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Book Description
Today having an excellent book with an great idea isn't enough for success. Over 2,000,000 books published every year, don't expect the crowd to pick up your book and say "it is a masterwork" even if it is. I swear you won't find any marketing bullshit in this book: No "social media is the king" crap No "just order a gold marketing package" and problem is solved No "do a giveaway" or "kindle free promotion" and everybody will buy your book I collected all the working marketing steps for those who want to make an impact with their books. You won't find any of the words "strategy" or "planning" in this book. I'm a practical guy and so I try to keep the bullshit and time-wasting things away from you, but I deeply believe that there are methods that should be shared with the new authors who have limited resources to do marketing. I'm focusing mainly on KDP authors, since it is the best platform to publish indie books in 2019. You will find small steps (not time-consuming), and some bigger steps in this short book which will be effective in long term. I tried to keep these steps in a linear timeline as it may happen even in real life. I hope you will enjoy reading this book, and you will find some useful resources and unique tactics that will raise your book out from the crowd.
Author: Michelle Zimmerman
Publisher: International Society for Technology in Education
ISBN: 1564847284
Category : Education
Languages : en
Pages : 217
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Book Description
Get the tools, resources and insights you need to explore artificial intelligence in the classroom and explore what students need to know about living in a world with AI. For many, artificial intelligence, or AI, may seem like science fiction, or inherently overwhelming. The reality is that AI is already being applied in industry and, for many of us, in our daily lives as well. A better understanding of AI can help you make informed decisions in the classroom that will impact the future of your students. Drawing from a broad variety of expert voices from countries including Australia, Japan, and South Africa, as well as educators from around the world and underrepresented student voices, this book explores some of the ways AI can improve education. These include educating learners about AI, teaching them about living in a world where they will be surrounded by AI and helping educators understand how they can use AI to augment human ability. Each chapter offers activities and questions to help you deepen your understanding, try out new concepts and reflect on the information presented. Links to media artifacts from trusted sources will help make your learning experience more dynamic while also providing additional resources to use in your classroom. This book: • Offers a unique approach to the topic, with chapter opening scenes, case studies, and featured student voices. • Discusses a variety of ways to teach students about AI, through design thinking, project-based learning and STEM connections. • Includes lesson ideas, activities and tools for exploring AI with your students. • Includes references to films and other media you can use in class to start discussions on AI or inspire design thinking and STEM projects. In Teaching AI, you’ll learn what AI is, how it works and how to use it to better prepare students in a world with increased human-computer interaction.
Author: Jake L Kent
Publisher: Jake L Kent
ISBN:
Category : Computers
Languages : en
Pages : 277
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Book Description
ChatGPT 4 $10,000 Per Month ChatGPT 4 $10,000 Per Month is a captivating and comprehensive journey into the world of AI-driven technologies, centered around the powerful language model, ChatGPT. This book is a must-listen for aspiring entrepreneurs, content creators, and professionals seeking to capitalize on the vast opportunities that AI presents. From the very first chapter, listeners are introduced to the wonders of ChatGPT and its limitless potential. The book covers the fundamentals of AI and natural language processing, providing listeners with a solid understanding of the technology that drives ChatGPT's capabilities. Practicality and hands-on learning take center stage as the book guides readers through setting up ChatGPT and customizing it to meet their business needs. The art of writing effective prompts and crafting engaging conversations with AI is explored, empowering readers to create compelling AI interactions. As the journey unfolds, listeners are equipped with a myriad of strategies for monetizing their skills and knowledge with ChatGPT. From freelancing on AI platforms to building personal websites and partnering with businesses, the book unveils various avenues for generating income through AI-driven conversations. ChatGPT Cashflow Are you tired of the daily grind, yearning for a life of financial independence and flexibility? Look no further! This groundbreaking playbook unveils the untapped power of ChatGPT, the cutting-edge language model that has revolutionized the world of AI. Inside this captivating guide, you'll discover a treasure trove of strategies, tips, and real-world examples that will empower you to break free from the traditional 9-to-5 drudgery and pave the way towards a life of abundant wealth and leisure. Learn how to leverage ChatGPT to generate passive income effortlessly. Unravel the step-by-step methods to create captivating chatbots, AI-powered content creation systems, and interactive virtual assistants that cater to a multitude of industries. Dive into the secrets of engaging conversational design and effective marketing techniques that will magnetize customers and clients like never before. But the benefits don't end there! This playbook goes beyond the realms of mere financial gains. Discover how nurturing an AI-driven business can provide you with the freedom to pursue your passions, spend quality time with loved ones, and indulge in life's greatest joys. ChatGPT For Business In an era where AI is redefining industries, businesses are presented with unprecedented opportunities for growth and innovation. "ChatGPT For Business" unveils a comprehensive guide for harnessing the power of AI, specifically ChatGPT, to drive revenue, enhance customer engagement, and revolutionize operations. This book delves into the strategic integration of ChatGPT to generate revenue like never before. From personalized customer interactions to AI-powered content creation, you'll explore practical techniques that leverage AI to captivate audiences, drive conversions, and create new monetization strategies. Discover how AI interactions with ChatGPT enhance customer engagement and deliver seamless experiences. Dive into the realm of hyper-personalization, where AI-driven insights provide tailored recommendations and interactions that resonate with individual preferences. Explore the art of automating content creation using ChatGPT. Learn how to maintain a consistent and high-quality content output that resonates with your audience across platforms, saving time while keeping your brand voice intact.
Author: Wayne Holmes
Publisher:
ISBN: 9781794293700
Category : Computers
Languages : en
Pages : 244
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Book Description
"The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book "Artificial Intelligence in Education, Promises and Implications for Teaching and Learning" by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant." --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) "The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: "We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue."I commend this book to anyone concerned with the future of education in a digital world." --Marc Durando, Executive Director, European Schoolnet
Author: Andrew Freed
Publisher: Simon and Schuster
ISBN: 1617298832
Category : Computers
Languages : en
Pages : 318
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Book Description
Design, develop, and deploy human-like AI solutions that chat with your customers, solve their problems, and streamline your support services. In Conversational AI, you will learn how to: Pick the right AI assistant type and channel for your needs Write dialog with intentional tone and specificity Train your AI’s classifier from the ground up Create question-and-direct-response AI assistants Design and optimize a process flow for web and voice Test your assistant’s accuracy and plan out improvements Conversational AI: Chatbots that work teaches you to create the kind of AI-enabled assistants that are revolutionizing the customer service industry. You’ll learn to build effective conversational AI that can automate common inquiries and easily address your customers' most common problems. This engaging and entertaining book delivers the essential technical and creative skills for designing successful AI solutions, from coding process flows and training machine learning, to improving your written dialog. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Create AI-driven chatbots and other intelligent agents that humans actually enjoy talking to! Adding intelligence to automated response systems saves time and money for you and your customers. Conversational AI systems excel at routine tasks such as answering common questions, classifying issues, and routing customers to the appropriate human staff. This book will show you how to build effective, production-ready AI assistants. About the book Conversational AI is a guide to creating AI-driven voice and text agents for customer support and other conversational tasks. This practical and entertaining book combines design theory with techniques for building and training AI systems. In it, you’ll learn how to find training data, assess performance, and write dialog that sounds human. You’ll go from building simple chatbots to designing the voice assistant for a complete call center. What's inside Pick the right AI for your needs Train your AI classifier Create question-and-direct-response assistants Design and optimize a process flow About the reader For software developers. Examples use Watson Assistant and Python. About the author Andrew R. Freed is a Master Inventor and Senior Technical Staff Member at IBM. He has worked in AI solutions since 2012. Table of Contents PART 1 FOUNDATIONS 1 Introduction to conversational AI 2 Building your first conversational AI PART 2 DESIGNING FOR SUCCESS 3 Designing effective processes 4 Designing effective dialogue 5 Building a successful AI assistant PART 3 TRAINING AND TESTING 6 Training your assistant 7 How accurate is your assistant? 8 Testing your dialogue flows PART 4 MAINTENANCE 9 Deployment and management 10 Improving your assistant PART 5 ADVANCED/OPTIONAL TOPICS 11 Building your own classifier 12 Additional training for voice assistants
Author: Denis Rothman
Publisher: Packt Publishing Ltd
ISBN: 1839212810
Category : Computers
Languages : en
Pages : 579
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Book Description
Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook Description 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. What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google TranslateUnderstand chained algorithms combining unsupervised learning with decision treesSolve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graphLearn about meta learning models with hybrid neural networksCreate a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data loggingBuilding conversational user interfaces (CUI) for chatbotsWriting genetic algorithms that optimize deep learning neural networksBuild quantum computing circuitsWho this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.
Author: Lorien Pratt
Publisher: Emerald Publishing Limited
ISBN: 9781787696549
Category : Computers
Languages : en
Pages : 0
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Book Description
Why aren't the most powerful new technologies being used to solve the world's most important problems: hunger, poverty, conflict, employment, disease? In Link, Dr. Lorien Pratt answers these questions by exploring the solution that is emerging worldwide to take Artificial Intelligence to the next level: Decision Intelligence.
Author: Florian Jaton
Publisher: MIT Press
ISBN: 0262542145
Category : Computers
Languages : en
Pages : 401
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Book Description
A laboratory study that investigates how algorithms come into existence. Algorithms--often associated with the terms big data, machine learning, or artificial intelligence--underlie the technologies we use every day, and disputes over the consequences, actual or potential, of new algorithms arise regularly. In this book, Florian Jaton offers a new way to study computerized methods, providing an account of where algorithms come from and how they are constituted, investigating the practical activities by which algorithms are progressively assembled rather than what they may suggest or require once they are assembled.
