Download or read book Artificial Intelligence Driven by Machine Learning and Deep Learning written by Bahman Zohuri and published by Nova Science Publishers. This book was released on 2020 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--

Download or read book Artificial Intelligence Driven by Machine Learning and Deep Learning written by Bahman Zohuri and published by Nova Science Publishers. This book was released on 2020 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Toward Artificial General Intelligence written by Victor Hugo C. de Albuquerque and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-11-06 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Low Code AI written by Gwendolyn Stripling and published by "O'Reilly Media, Inc.". This book was released on 2023-09-13 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data; feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to: Distinguish between structured and unstructured data and the challenges they present Visualize and analyze data Preprocess data for input into a machine learning model Differentiate between the regression and classification supervised learning models Compare different ML model types and architectures, from no code to low code to custom training Design, implement, and tune ML models Export data to a GitHub repository for data management and governance

Download or read book Artificial Intelligence Driven Geographies written by Seyed Navid Mashhadi Moghaddam and published by Springer Nature. This book was released on with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence and Machine Learning written by Andrew D. Chapman and published by The Autodidact’s Toolkit. This book was released on 2023-12-06 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Malware Analysis Using Artificial Intelligence and Deep Learning written by Mark Stamp and published by Springer Nature. This book was released on 2020-12-20 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​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.

Download or read book AI and ML for Coders written by Andrew Hinton and published by Book Bound Studios. This book was released on 2024-01-04 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you ready to unlock the transformative power of Artificial Intelligence (AI) and Machine Learning (ML) in your coding projects? "AI and ML for Coders" is the essential guide for coders who want to leap into the future of technology. This book is tailored for programmers, developers, and tech enthusiasts eager to integrate AI and ML into their work. Whether you're a seasoned coder or just starting, you'll find invaluable insights and practical knowledge to elevate your craft. Here's what you'll gain from "AI and ML for Coders": - A comprehensive understanding of AI and ML evolution, from historical milestones to cutting-edge techniques. - A deep dive into the core concepts, terminology, and ethical considerations that every coder must know. - Hands-on guidance on choosing the right tools, libraries, and programming languages for your AI and ML projects. - Expert strategies for data preparation, preprocessing, and selecting the most effective algorithms for different tasks. - Real-world applications and case studies demonstrate AI and ML's power in coding. Key features include: - Clear explanations of supervised, unsupervised, and reinforcement learning. - Exploration of neural networks, deep learning, natural language processing, and computer vision. - Practical advice on navigating the ethical landscape of AI to develop responsible and trustworthy applications. Authored by a seasoned expert in the field, "AI and ML for Coders" is your roadmap to mastering AI and ML. It's not just a book; it's an investment in your future as a coder in an AI-driven world. Take advantage of the opportunity to be at the forefront of the AI revolution. Take the next step and add "AI and ML for Coders" to your library today. Your journey into the realm of AI and ML starts here!

Download or read book Applying Data Science written by Arthur K. Kordon and published by Springer Nature. This book was released on 2020-09-12 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence and Deep Learning in Pathology written by Stanley Cohen and published by Elsevier Health Sciences. This book was released on 2020-06-02 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.

Download or read book Next Generation AI Language Models in Research written by Kashif Naseer Qureshi and published by CRC Press. This book was released on 2024-11-13 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this comprehensive and cutting-edge volume, Qureshi and Jeon bring together experts from around the world to explore the potential of artificial intelligence models in research and discuss the potential benefits and the concerns and challenges that the rapid development of this field has raised. The international chapter contributor group provides a wealth of technical information on different aspects of AI, including key aspects of AI, deep learning and machine learning models for AI, natural language processing and computer vision, reinforcement learning, ethics and responsibilities, security, practical implementation, and future directions. The contents are balanced in terms of theory, methodologies, and technical aspects, and contributors provide case studies to clearly illustrate the concepts and technical discussions throughout. Readers will gain valuable insights into how AI can revolutionize their work in fields including data analytics and pattern identification, healthcare research, social science research, and more, and improve their technical skills, problem-solving abilities, and evidence-based decision-making. Additionally, they will be cognizant of the limitations and challenges, the ethical implications, and security concerns related to language models, which will enable them to make more informed choices regarding their implementation. This book is an invaluable resource for undergraduate and graduate students who want to understand AI models, recent trends in the area, and technical and ethical aspects of AI. Companies involved in AI development or implementing AI in various fields will also benefit from the book’s discussions on both the technical and ethical aspects of this rapidly growing field.

Download or read book Deep Learning Practical Neural Networks with Java written by Yusuke Sugomori and published by Packt Publishing Ltd. This book was released on 2017-06-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book The Ultimate Modern Guide to Artificial Intelligence written by Enamul Haque and published by . This book was released on 2023-03-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book AI Decoded written by Bear Brown and published by BrOwn eBook Publications. This book was released on 2024-03-01 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Deep Learning written by John D. Kelleher and published by MIT Press. This book was released on 2019-09-10 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.

Download or read book The Future of Artificial Intelligence and Robotics written by David Pastor-Escuredo and published by Springer Nature. This book was released on with total page 837 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning Applications Volume 2 written by M. Arif Wani and published by Springer. This book was released on 2020-12-14 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.