Artificial Intelligence Driven By Machine Learning And Deep Learning PDF Download
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| Author | : Bahman Zohuri |
| Publisher | : Nova Science Publishers |
| Total Pages | : 455 |
| Release | : 2020 |
| Genre | : Computers |
| ISBN | : 9781536183672 |
Download Artificial Intelligence Driven by Machine Learning and Deep Learning Book in PDF, ePub and Kindle
"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"--
| Author | : Bahman Zohuri |
| Publisher | : Nova Science Publishers |
| Total Pages | : 455 |
| Release | : 2020 |
| Genre | : Artificial intelligence |
| ISBN | : 9781536183146 |
Download Artificial Intelligence Driven by Machine Learning and Deep Learning Book in PDF, ePub and Kindle
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.
| Author | : Victor Hugo C. de Albuquerque |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 520 |
| Release | : 2023-11-06 |
| Genre | : Computers |
| ISBN | : 3111324168 |
Download Toward Artificial General Intelligence Book in PDF, ePub and Kindle
| Author | : Stanley Cohen |
| Publisher | : Elsevier Health Sciences |
| Total Pages | : 290 |
| Release | : 2020-06-02 |
| Genre | : Medical |
| ISBN | : 0323675379 |
Download Artificial Intelligence and Deep Learning in Pathology Book in PDF, ePub and Kindle
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.
| Author | : Bear Brown |
| Publisher | : BrOwn eBook Publications |
| Total Pages | : 172 |
| Release | : 2024-03-01 |
| Genre | : Computers |
| ISBN | : |
Download AI Decoded Book in PDF, ePub and Kindle
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.
| Author | : Andrew Hinton |
| Publisher | : Book Bound Studios |
| Total Pages | : 171 |
| Release | : 2024-01-04 |
| Genre | : Computers |
| ISBN | : 1761590030 |
Download AI and ML for Coders Book in PDF, ePub and Kindle
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!
| Author | : Andrew D. Chapman |
| Publisher | : The Autodidact’s Toolkit |
| Total Pages | : 452 |
| Release | : 2023-12-06 |
| Genre | : Computers |
| ISBN | : |
Download Artificial Intelligence and Machine Learning Book in PDF, ePub and Kindle
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.
| Author | : Arthur K. Kordon |
| Publisher | : Springer Nature |
| Total Pages | : 511 |
| Release | : 2020-09-12 |
| Genre | : Computers |
| ISBN | : 3030363759 |
Download Applying Data Science Book in PDF, ePub and Kindle
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.
| Author | : Mark Stamp |
| Publisher | : Springer Nature |
| Total Pages | : 651 |
| Release | : 2020-12-20 |
| Genre | : Computers |
| ISBN | : 3030625826 |
Download Malware Analysis Using Artificial Intelligence and Deep Learning Book in PDF, ePub and Kindle
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.
| Author | : Zsolt Nagy |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 330 |
| Release | : 2018-12-12 |
| Genre | : Computers |
| ISBN | : 1789809207 |
Download Artificial Intelligence and Machine Learning Fundamentals Book in PDF, ePub and Kindle
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).
