Cutting Edge Artificial Intelligence
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Cutting Edge Artificial Intelligence
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Author : Anna Leigh
language : en
Publisher: Lerner Publications
Release Date : 2018-08
Cutting Edge Artificial Intelligence written by Anna Leigh and has been published by Lerner Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08 with Juvenile Nonfiction categories.
Filled with cool photos and information about the latest in artificial intelligence technology, this book shows readers how AI has developed, how it is used, and how it will continue to develop for the future--
The The Reinforcement Learning Workshop
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Author : Alessandro Palmas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-18
The The Reinforcement Learning Workshop written by Alessandro Palmas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Computers categories.
Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide Key FeaturesUse TensorFlow to write reinforcement learning agents for performing challenging tasksLearn how to solve finite Markov decision problemsTrain models to understand popular video games like BreakoutBook Description Various intelligent applications such as video games, inventory management software, warehouse robots, and translation tools use reinforcement learning (RL) to make decisions and perform actions that maximize the probability of the desired outcome. This book will help you to get to grips with the techniques and the algorithms for implementing RL in your machine learning models. Starting with an introduction to RL, you’ll be guided through different RL environments and frameworks. You’ll learn how to implement your own custom environments and use OpenAI baselines to run RL algorithms. Once you’ve explored classic RL techniques such as Dynamic Programming, Monte Carlo, and TD Learning, you’ll understand when to apply the different deep learning methods in RL and advance to deep Q-learning. The book will even help you understand the different stages of machine-based problem-solving by using DARQN on a popular video game Breakout. Finally, you’ll find out when to use a policy-based method to tackle an RL problem. By the end of The Reinforcement Learning Workshop, you’ll be equipped with the knowledge and skills needed to solve challenging problems using reinforcement learning. What you will learnUse OpenAI Gym as a framework to implement RL environmentsFind out how to define and implement reward functionExplore Markov chain, Markov decision process, and the Bellman equationDistinguish between Dynamic Programming, Monte Carlo, and Temporal Difference LearningUnderstand the multi-armed bandit problem and explore various strategies to solve itBuild a deep Q model network for playing the video game BreakoutWho this book is for If you are a data scientist, machine learning enthusiast, or a Python developer who wants to learn basic to advanced deep reinforcement learning algorithms, this workshop is for you. A basic understanding of the Python language is necessary.
The Ai Advantage
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Author : Thomas H. Davenport
language : en
Publisher: MIT Press
Release Date : 2019-08-06
The Ai Advantage written by Thomas H. Davenport and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-06 with Business & Economics categories.
Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage. In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient. Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise. Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI. A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review.
The Artificial Intelligence Infrastructure Workshop
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Author : Chinmay Arankalle
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-17
The Artificial Intelligence Infrastructure Workshop written by Chinmay Arankalle and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-17 with Computers categories.
Explore how a data storage system works – from data ingestion to representation Key FeaturesUnderstand how artificial intelligence, machine learning, and deep learning are different from one anotherDiscover the data storage requirements of different AI apps using case studiesExplore popular data solutions such as Hadoop Distributed File System (HDFS) and Amazon Simple Storage Service (S3)Book Description Social networking sites see an average of 350 million uploads daily - a quantity impossible for humans to scan and analyze. Only AI can do this job at the required speed, and to leverage an AI application at its full potential, you need an efficient and scalable data storage pipeline. The Artificial Intelligence Infrastructure Workshop will teach you how to build and manage one. The Artificial Intelligence Infrastructure Workshop begins taking you through some real-world applications of AI. You'll explore the layers of a data lake and get to grips with security, scalability, and maintainability. With the help of hands-on exercises, you'll learn how to define the requirements for AI applications in your organization. This AI book will show you how to select a database for your system and run common queries on databases such as MySQL, MongoDB, and Cassandra. You'll also design your own AI trading system to get a feel of the pipeline-based architecture. As you learn to implement a deep Q-learning algorithm to play the CartPole game, you'll gain hands-on experience with PyTorch. Finally, you'll explore ways to run machine learning models in production as part of an AI application. By the end of the book, you'll have learned how to build and deploy your own AI software at scale, using various tools, API frameworks, and serialization methods. What you will learnGet to grips with the fundamentals of artificial intelligenceUnderstand the importance of data storage and architecture in AI applicationsBuild data storage and workflow management systems with open source toolsContainerize your AI applications with tools such as DockerDiscover commonly used data storage solutions and best practices for AI on Amazon Web Services (AWS)Use the AWS CLI and AWS SDK to perform common data tasksWho this book is for If you are looking to develop the data storage skills needed for machine learning and AI and want to learn AI best practices in data engineering, this workshop is for you. Experienced programmers can use this book to advance their career in AI. Familiarity with programming, along with knowledge of exploratory data analysis and reading and writing files using Python will help you to understand the key concepts covered.
Artificial Intelligence
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Author : Kathryn Hulick
language : en
Publisher: ABDO
Release Date : 2015-12-15
Artificial Intelligence written by Kathryn Hulick and has been published by ABDO this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-15 with Juvenile Nonfiction categories.
Thrilling new discoveries in science and technology are announced almost daily. Cutting-Edge Science and Technology keeps readers at the forefront of new research. Artificial Intelligencecovers a wide variety of topics in the emerging field of machine learning, including facial identification, voice recognition, video games, driverless cars, and robot helpers. High-impact photos and explanatory graphics and charts bring scientific concepts to life. Features include essential facts, a glossary, selected bibliography, websites, source notes, and an index. Aligned to Common Core Standards and correlated to state standards. Essential Library is an imprint of Abdo Publishing, a division of ABDO.
Artificial Intelligence And Deep Learning For Decision Makers
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Author : Dr. Jagreet Kaur
language : en
Publisher: BPB Publications
Release Date : 2019-12-28
Artificial Intelligence And Deep Learning For Decision Makers written by Dr. Jagreet Kaur and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-28 with Computers categories.
Learn modern-day technologies from modern-day technical giants DESCRIPTIONÊ The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations.Ê The first two chapters describe the introduction of the artificial intelligence and deep learning methods. In the first chapter, the concept of human thinking process, starting from the biochemical responses within the structure of neurons to the problem-solving steps through computational thinking skills are discussed. All chapters after the first two should be considered as the study of different technological and Artificial Intelligence giants of current age. These chapters are placed in a way that each chapter could be considered a separate study of a separate company, which includes the achievements of intelligent services currently provided by the company, discussion on the business model of the company towards the use of the deep learning technologies, the advancement of the web services which are incorporated with intelligent capability introduced by company, the efforts of the company in contributing to the development of the artificial intelligence and deep learning research. KEY FEATURES Real-world success and failure stories of artificial intelligence explained Understand concepts of artificial intelligence and deep learning methodsÊ Learn how to use artificial intelligence and deep learning methods Know how to prepare dataset and implement models using industry leading Python packagesÊ YouÕll be able to apply and analyze the results produced by the models for prediction WHAT WILL YOU LEARN How to use the algorithms written in the Python programming language to design models and perform predictions in general datasets Understand use cases in different industries related to the implementation of artificial intelligence and deep learning methods Learn the use of potential ideas in artificial intelligence and deep learning methods to improve the operational processes or new products and how services can be produced based on the methods WHO THIS BOOK IS FORÊ This book is targeted to business and organization leaders, technology enthusiasts, professionals, and managers who seek knowledge of artificial intelligence and deep learning methods. Table of Contents Artificial Intelligence and Deep Learning Data Science for Business Analysis Decision Making Intelligent Computing Strategies By GoogleÊ Cognitive Learning Services in IBM Watson Advancement web services by BaiduÊ Improved Social Business by Facebook Personalized Intelligent Computing by Apple Cloud Computing Intelligent by Microsoft
Machine Learning
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Author : Brian L. Taylor
language : en
Publisher:
Release Date : 2019-07-07
Machine Learning written by Brian L. Taylor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-07 with categories.
★★★ Buy the Paperback version and then get the Kindle Book versions for FREE ★★★ Do you want to know, How to work with Robot Program? Do you want to become an expert Robot/Machine Programmer? And impress your friends with the programs you can make from scratch, Then you are on the right way and keep reading this Machine Learning book. From self-driving cars, recommendation systems to face and voice recognition, machine learning is the direction of the future. Would you choose to learn the mathematics behind machine learning to enter the fields of data analysis and artificial intelligence? There are not many resources that give detailed and straightforward examples and that go step by step through the topics of machine learning. If you are read this "Machine Learning: a quick guide to Artificial Intelligence, Neural Network and Cutting Edge Deep Learning Techniques for beginners", you are at the right place. This book not only explains what kind of mathematics is involved and the confusing notation, but also directly presents the fundamental topics of machine learning. This book will help you to learn smoothly and naturally, that will prepare you for more advanced topics besides taking away the belief that machine learning is complicated and difficult. In this book, you will attain helpful information for getting started, such as: Criteria that help distinguish tasks that are suitable for machine Supervised Machine Learning Neural Networks Unsupervised Machine Learning Learning by Reinforcement Neural Networks Neural Networks versus Conventional Computers Deep Learning Supervised Modes and Unsupervised Modes Running Python Getting Started Artificial Intelligence, Machine Learning, and Deep Learning The Future Promise of Artificial Intelligence and deep learning and more How many hours of your life are you willing to waste to gather partial or false information when you can get everything you require to REACH YOUR GOALS by reading this fantastic guide. Get Your Copy Now! Scroll Up and Click the Buy Now Button And Enjoy!
Artificial Intelligence
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Author : Betsy Rathburn
language : en
Publisher: Bellwether Media
Release Date : 2020-08-01
Artificial Intelligence written by Betsy Rathburn and has been published by Bellwether Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-01 with Juvenile Nonfiction categories.
Artificial intelligence is all around us! It’s in our classrooms, hospitals, and even in the smartphones in our pockets. But how does this technology work, where did it come from, and what will it bring in the future? Readers will discover the answers to these questions and more in this high-interest title packed with information. Engaging text and photos will pull readers in, and a diagram, timeline, graph, and pro/con comparison will highlight even more about artificial intelligence!
Artificial Intelligence In Financial Markets
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Author : Christian L. Dunis
language : en
Publisher: Springer
Release Date : 2016-11-21
Artificial Intelligence In Financial Markets written by Christian L. Dunis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Business & Economics categories.
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
An Introduction To Artificial Intelligence In Education
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Author : Shengquan Yu
language : en
Publisher: Springer Nature
Release Date : 2021-11-29
An Introduction To Artificial Intelligence In Education written by Shengquan Yu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Education categories.
This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds. The book provides an essential resource for researchers, students and industrial practitioners interested and engaged in the fields of AI and education. It also offers a convenient handbook for non-professional readers who need a primer on AI in education, and who want to gain a deeper understanding of emerging trends in this domain.