Artificial Intelligence Driven By Machine Learning And Deep Learning

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Artificial Intelligence Driven by Machine Learning and Deep Learning

Author : Bahman Zohuri,Siamak Zadeh
Publisher : Nova Science Publishers
Page : 455 pages
File Size : 46,6 Mb
Release : 2020
Category : Computers
ISBN : 1536183679

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Artificial Intelligence Driven by Machine Learning and Deep Learning by Bahman Zohuri,Siamak Zadeh Pdf

"The future of any business from banking, e-commerce, real estate, homeland security, healthcare, marketing, the stock market, manufacturing, education, retail to government organizations depends on the data and analytics capabilities that are built and scaled. The speed of change in technology in recent years has been a real challenge for all businesses. To manage that, a significant number of organizations are exploring the BigData (BD) infrastructure that helps them to take advantage of new opportunities while saving costs. Timely transformation of information is also critical for the survivability of an organization. Having the right information at the right time will enhance not only the knowledge of stakeholders within an organization but also providing them with a tool to make the right decision at the right moment. It is no longer enough to rely on a sampling of information about the organizations' customers. The decision-makers need to get vital insights into the customers' actual behavior, which requires enormous volumes of data to be processed. We believe that Big Data infrastructure is the key to successful Artificial Intelligence (AI) deployments and accurate, unbiased real-time insights. Big data solutions have a direct impact and changing the way the organization needs to work with help from AI and its components ML and DL. In this article, we discuss these topics"--

Toward Artificial General Intelligence

Author : Victor Hugo C. de Albuquerque,Pethuru Raj,Satya Prakash Yadav
Publisher : Walter de Gruyter GmbH & Co KG
Page : 520 pages
File Size : 42,9 Mb
Release : 2023-11-06
Category : Computers
ISBN : 9783111324166

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Toward Artificial General Intelligence by Victor Hugo C. de Albuquerque,Pethuru Raj,Satya Prakash Yadav Pdf

Applying Data Science

Author : Arthur K. Kordon
Publisher : Springer Nature
Page : 511 pages
File Size : 46,8 Mb
Release : 2020-09-12
Category : Computers
ISBN : 9783030363758

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Applying Data Science by Arthur K. Kordon Pdf

This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: machine learning, deep learning, decision trees and random forests, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem knowledge acquisition, data preparation, data analysis, model development, and model deployment lifecycle. Finally, in Part III the author illustrates the power of AI-based data science with successful applications in manufacturing and business. He also shows how to introduce this technology in a business setting and guides the reader on how to build the appropriate infrastructure and develop the required skillsets. The book is ideal for data scientists who will implement the proposed methodology and techniques in their projects. It is also intended to help business leaders and entrepreneurs who want to create competitive advantage by using AI-based data science, as well as academics and students looking for an industrial view of this discipline.

Artificial Intelligence and Machine Learning Fundamentals

Author : Zsolt Nagy
Publisher : Packt Publishing Ltd
Page : 330 pages
File Size : 55,6 Mb
Release : 2018-12-12
Category : Computers
ISBN : 9781789809206

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Artificial Intelligence and Machine Learning Fundamentals by Zsolt Nagy Pdf

Create AI applications in Python and lay the foundations for your career in data science Key FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook 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 learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho 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).

The Ultimate Modern Guide to Artificial Intelligence

Author : Enamul Haque
Publisher : Unknown
Page : 0 pages
File Size : 47,7 Mb
Release : 2023-03-09
Category : Electronic
ISBN : 1447805313

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The Ultimate Modern Guide to Artificial Intelligence by Enamul Haque Pdf

This book is your ultimate guide to understanding the revolutionary technology of Artificial Intelligence (AI). This book covers everything from the basics of AI to its profound impact on various industries, such as healthcare, transportation, banking, and entertainment. You will discover the endless possibilities of AI and how it is changing our lives for the better. The book begins with an introduction to AI and its significance in the modern world. You will learn about the various applications of AI, including speech recognition assistants, image recognition, and biometric data analysis. This will give you a comprehensive understanding of how AI is used in our daily lives and the different industries benefiting from its advancements. In the following chapters, you will delve deeper into the workings of AI, machine learning, deep learning, neural networks, and natural language generation. The book explains how these technologies function and how they are applied in real-life scenarios. You will also gain insights into the differences between human and machine intelligence, providing a holistic understanding of AI's capabilities and limitations. Whether you are a business decision-maker, an IT professional, or someone who is merely interested in the impact of AI on the world, this book is a must-read. With its easy-to-understand language and numerous examples, it empowers you to comprehend the complex technology of AI and be part of the conversation shaping our future.

AI Decoded

Author : Bear Brown
Publisher : BrOwn eBook Publications
Page : 172 pages
File Size : 52,5 Mb
Release : 2024-03-01
Category : Computers
ISBN : 8210379456XXX

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AI Decoded by Bear Brown Pdf

Embark on a captivating journey through the boundless realm of artificial intelligence with "AI Decoded: Exploring the Depths of Artificial Intelligence." In this illuminating guide, readers will delve into the intricate inner workings of AI, from foundational concepts like machine learning and neural networks to cutting-edge developments in deep learning and quantum computing. Navigate the ethical and societal implications of AI deployment, uncover practical applications across diverse industries, and gain insights into future trends shaping our world. With clarity and depth, this book demystifies the complexities of AI, empowering readers to grasp its transformative potential and navigate the evolving landscape of intelligent technology.

Malware Analysis Using Artificial Intelligence and Deep Learning

Author : Mark Stamp,Mamoun Alazab,Andrii Shalaginov
Publisher : Springer Nature
Page : 651 pages
File Size : 51,6 Mb
Release : 2020-12-20
Category : Computers
ISBN : 9783030625825

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Malware Analysis Using Artificial Intelligence and Deep Learning by Mark Stamp,Mamoun Alazab,Andrii Shalaginov Pdf

​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.

TensorFlow 1.x Deep Learning Cookbook

Author : Antonio Gulli,Amita Kapoor
Publisher : Packt Publishing Ltd
Page : 526 pages
File Size : 40,9 Mb
Release : 2017-12-12
Category : Computers
ISBN : 9781788291866

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TensorFlow 1.x Deep Learning Cookbook by Antonio Gulli,Amita Kapoor Pdf

Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book Skill up and implement tricky neural networks using Google's TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment Who This Book Is For This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful. What You Will Learn Install TensorFlow and use it for CPU and GPU operations Implement DNNs and apply them to solve different AI-driven problems. Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code. Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box. Use different regression techniques for prediction and classification problems Build single and multilayer perceptrons in TensorFlow Implement CNN and RNN in TensorFlow, and use it to solve real-world use cases. Learn how restricted Boltzmann Machines can be used to recommend movies. Understand the implementation of Autoencoders and deep belief networks, and use them for emotion detection. Master the different reinforcement learning methods to implement game playing agents. GANs and their implementation using TensorFlow. In Detail Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life problems in artificial intelligence domain. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow. With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work. You will learn the performance of different DNNs on some popularly used data sets such as MNIST, CIFAR-10, Youtube8m, and more. You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. Get a sneak peek of TPU architecture and how they will affect DNN future. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more. Style and approach This book consists of hands-on recipes where you'll deal with real-world problems. You'll execute a series of tasks as you walk through data mining challenges using TensorFlow 1.x. Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Author : K. Gayathri Devi,Mamata Rath,Nguyen Thi Dieu Linh
Publisher : CRC Press
Page : 255 pages
File Size : 50,5 Mb
Release : 2020-10-08
Category : Computers
ISBN : 9781000179538

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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches by K. Gayathri Devi,Mamata Rath,Nguyen Thi Dieu Linh Pdf

Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning

Artificial Intelligence and Machine Learning for EDGE Computing

Author : Rajiv Pandey,Sunil Kumar Khatri,Neeraj Kumar Singh,Parul Verma
Publisher : Academic Press
Page : 516 pages
File Size : 44,8 Mb
Release : 2022-04-26
Category : Science
ISBN : 9780128240557

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Artificial Intelligence and Machine Learning for EDGE Computing by Rajiv Pandey,Sunil Kumar Khatri,Neeraj Kumar Singh,Parul Verma Pdf

Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints

Deep Learning: Practical Neural Networks with Java

Author : Yusuke Sugomori,Bostjan Kaluza,Fabio M. Soares,Alan M. F. Souza
Publisher : Packt Publishing Ltd
Page : 744 pages
File Size : 43,5 Mb
Release : 2017-06-08
Category : Computers
ISBN : 9781788471718

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Deep Learning: Practical Neural Networks with Java by Yusuke Sugomori,Bostjan Kaluza,Fabio M. Soares,Alan M. F. Souza Pdf

Build and run intelligent applications by leveraging key Java machine learning libraries About This Book Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications This step-by-step guide will help you solve real-world problems and links neural network theory to their application Who This Book Is For This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life. What You Will Learn Get a practical deep dive into machine learning and deep learning algorithms Explore neural networks using some of the most popular Deep Learning frameworks Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts, algorithms, and the toolbox for deep learning Select and split data sets into training, test, and validation, and explore validation strategies Apply the code generated in practical examples, including weather forecasting and pattern recognition In Detail Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work. The course provides you with highly practical content explaining deep learning with Java, from the following Packt books: Java Deep Learning Essentials Machine Learning in Java Neural Network Programming with Java, Second Edition Style and approach This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application

Practical Automated Machine Learning on Azure

Author : Deepak Mukunthu,Parashar Shah,Wee Hyong Tok
Publisher : "O'Reilly Media, Inc."
Page : 198 pages
File Size : 40,9 Mb
Release : 2019-09-23
Category : Computers
ISBN : 9781492055549

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Practical Automated Machine Learning on Azure by Deepak Mukunthu,Parashar Shah,Wee Hyong Tok Pdf

Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you’ll learn how to apply automated machine learning (AutoML), a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology. Building machine-learning models is an iterative and time-consuming process. Even those who know how to create ML models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply AutoML to your data right away. Learn how companies in different industries are benefiting from AutoML Get started with AutoML using Azure Explore aspects such as algorithm selection, auto featurization, and hyperparameter tuning Understand how data analysts, BI professions, developers can use AutoML in their familiar tools and experiences Learn how to get started using AutoML for use cases including classification, regression, and forecasting.

Humanity Driven AI

Author : Fang Chen,Jianlong Zhou
Publisher : Springer Nature
Page : 330 pages
File Size : 51,8 Mb
Release : 2021-12-01
Category : Computers
ISBN : 9783030721886

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Humanity Driven AI by Fang Chen,Jianlong Zhou Pdf

Artificial Intelligence (AI) is changing the world around us, and it is changing the way people are living, working, and entertaining. As a result, demands for understanding how AI functions to achieve and enhance human goals from basic needs to high level well-being (whilst maintaining human health) are increasing. This edited book systematically investigates how AI facilitates enhancing human needs in the digital age, and reports on the state-of-the-art advances in theories, techniques, and applications of humanity driven AI. Consisting of five parts, it covers the fundamentals of AI and humanity, AI for productivity, AI for well-being, AI for sustainability, and human-AI partnership. Humanity Driven AI creates an important opportunity to not only promote AI techniques from a humanity perspective, but also to invent novel AI applications to benefit humanity. It aims to serve as the dedicated source for the theories, methodologies, and applications on humanity driven AI, establishing state-of-the-art research, and providing a ground-breaking book for graduate students, research professionals, and AI practitioners.

Artificial Intelligence and Machine Learning

Author : Andrew D. Chapman
Publisher : The Autodidact’s Toolkit
Page : 452 pages
File Size : 45,8 Mb
Release : 2023-12-06
Category : Computers
ISBN : 8210379456XXX

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Artificial Intelligence and Machine Learning by Andrew D. Chapman Pdf

Are you ready to embark on a journey into the future of technology? Dive into the world of Artificial Intelligence (AI) and Machine Learning (ML) with this comprehensive guide that demystifies the complex and empowers you to harness the potential of intelligent machines. Begin your exploration by grasping the core concepts, history, and terminology of AI and ML. Discover the fascinating evolution of these transformative technologies and their real-world impact on diverse industries. Move beyond theory into practical applications. Learn how to build and optimize machine learning models, explore advanced techniques, and gain insights into the revolutionary realm of deep learning. Understand the ethical and societal implications of AI. Tackle issues of fairness, privacy, employment, and regulation, and learn how responsible AI practices can shape a better future. Discover the pivotal role of data in AI and ML. Explore data collection, preprocessing, big data, and visualization, and gain hands-on experience with real-world data science projects. Keep up with the latest advancements in AI technologies and platforms. Explore cloud-based services, edge computing, quantum computing, and the integration of AI with the Internet of Things (IoT). Learn how AI can transform your organization. Develop AI strategies, implement AI in marketing, supply chain, and HR, and gain insights into the future of business in the AI era. This book is your key to unlocking the limitless potential of AI and ML. Whether you're a student, professional, or enthusiast, you'll gain a holistic understanding of these game-changing technologies and be inspired to contribute to their ongoing evolution.

The Future of Artificial Intelligence

Author : R.H Rizvi
Publisher : R.H Rizvi
Page : 60 pages
File Size : 49,6 Mb
Release : 2024-06-14
Category : Computers
ISBN : 8210379456XXX

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The Future of Artificial Intelligence by R.H Rizvi Pdf

The Future of Artificial Intelligence delves into the transformative potential and profound implications of artificial intelligence on various facets of human life and industry. This comprehensive book explores the historical evolution of AI, the core technologies driving advancements, and the diverse applications across sectors such as healthcare, finance, education, and transportation. Each chapter meticulously examines the opportunities AI presents for innovation and societal impact, while also addressing the ethical considerations, privacy concerns, and economic disruptions associated with its rapid development. By integrating insights from experts and case studies, this book provides a balanced perspective on the promise and challenges of AI, offering readers a thoughtful analysis of how AI can shape a sustainable and inclusive future.