Download or read book ML NET Revealed written by Sudipta Mukherjee and published by Apress. This book was released on 2021-03-01 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get introduced to ML.NET, a new open source, cross-platform machine learning framework from Microsoft that is intended to democratize machine learning and enable as many developers as possible. Dive in to learn how ML.NET is designed to encapsulate complex algorithms, making it easy to consume them in many application settings without having to think about the internal details. You will learn about the features that do the necessary “plumbing” that is required in a variety of machine learning problems, freeing up your time to focus on your applications. You will understand that while the infrastructure pieces may at first appear to be disconnected and haphazard, they are not. Developers who are curious about trying machine learning, yet are shying away from it due to its perceived complexity, will benefit from this book. This introductory guide will help you make sense of it all and inspire you to try out scenarios and code samples that can be used in many real-world situations. What You Will Learn Create a machine learning model using only the C# language Build confidence in your understanding of machine learning algorithms Painlessly implement algorithms Begin using the ML.NET library software Recognize the many opportunities to utilize ML.NET to your advantage Apply and reuse code samples from the book Utilize the bonus algorithm selection quick references available online Who This Book Is For Developers who want to learn how to use and apply machine learning to enrich their applications

Download or read book Hybrid Intelligent Systems written by Ajith Abraham and published by Springer Nature. This book was released on 2023-05-24 with total page 1380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 97 selected papers from the 22nd International Conference on Hybrid Intelligent Systems (HIS 2022) and 26 papers from the 18th International Conference on Information Assurance and Security, which was held online, from 13 to 15 December 2022. A premier conference in the field of artificial intelligence and machine learning applications, HIS–IAS 2022, brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from over 35 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

Download or read book Applied Informatics for Industry 4 0 written by Nazmul Siddique and published by CRC Press. This book was released on 2023-02-17 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Informatics for Industry 4.0 combines the technologies of computer science and information science to assist in the management and processing of data to provide different types of services. Due to the adaptation of 4.0 IR-related technologies, applied informatics is playing a vital role in different sectors such as healthcare, complex system design and privacy-related issues. This book focuses on cutting edge research from the fields of informatics and complex industrial systems, and will cover topics including health informatics, bioinformatics, brain informatics, genomics and proteomics, data and network security and more. The text will appeal to beginners and advanced researchers in the fields of computer science, information sciences, electrical and electronic engineering and robotics.

Download or read book Computer Aided Drug Design CADD From Ligand Based Methods to Structure Based Approaches written by Mithun Rudrapal and published by Elsevier. This book was released on 2022-05-26 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer-Aided Drug Design (CADD): From Ligand-Based Methods to Structure-Based Approaches outlines the basic theoretical principles, methodologies and applications of different fundamental and advanced CADD approaches and techniques. Including information on current protocols as well as recent developments in the computational methods, tools and techniques used for rational drug design, the book explains the fundamental aspects of CADD, combining this with a practical understanding of the various in silico approaches used in modern drug discovery processes to assess the field in a comprehensive and systematic manner. Providing up-to-date, information and guidance for scientists, researchers, students and teachers, the book helps readers address specific academic and research related problems using illustrative explanations, examples and case studies, which are systematically reviewed. - Highlights in silico approaches to drug design and discovery using computational tools and techniques - Details ligand-based and structure-based drug design in a comprehensive and systematic approach - Summarizes recent developments in computational drug design strategy as novel approaches of rational drug designing

Download or read book Hands On Machine Learning with ML NET written by Jarred Capellman and published by Packt Publishing Ltd. This book was released on 2020-03-27 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET Core Key FeaturesGet well-versed with the ML.NET framework and its components and APIs using practical examplesLearn how to build, train, and evaluate popular machine learning algorithms with ML.NET offeringsExtend your existing machine learning models by integrating with TensorFlow and other librariesBook Description Machine learning (ML) is widely used in many industries such as science, healthcare, and research and its popularity is only growing. In March 2018, Microsoft introduced ML.NET to help .NET enthusiasts in working with ML. With this book, you’ll explore how to build ML.NET applications with the various ML models available using C# code. The book starts by giving you an overview of ML and the types of ML algorithms used, along with covering what ML.NET is and why you need it to build ML apps. You’ll then explore the ML.NET framework, its components, and APIs. The book will serve as a practical guide to helping you build smart apps using the ML.NET library. You’ll gradually become well versed in how to implement ML algorithms such as regression, classification, and clustering with real-world examples and datasets. Each chapter will cover the practical implementation, showing you how to implement ML within .NET applications. You’ll also learn to integrate TensorFlow in ML.NET applications. Later you’ll discover how to store the regression model housing price prediction result to the database and display the real-time predicted results from the database on your web application using ASP.NET Core Blazor and SignalR. By the end of this book, you’ll have learned how to confidently perform basic to advanced-level machine learning tasks in ML.NET. What you will learnUnderstand the framework, components, and APIs of ML.NET using C#Develop regression models using ML.NET for employee attrition and file classificationEvaluate classification models for sentiment prediction of restaurant reviewsWork with clustering models for file type classificationsUse anomaly detection to find anomalies in both network traffic and login historyWork with ASP.NET Core Blazor to create an ML.NET enabled web applicationIntegrate pre-trained TensorFlow and ONNX models in a WPF ML.NET application for image classification and object detectionWho this book is for If you are a .NET developer who wants to implement machine learning models using ML.NET, then this book is for you. This book will also be beneficial for data scientists and machine learning developers who are looking for effective tools to implement various machine learning algorithms. A basic understanding of C# or .NET is mandatory to grasp the concepts covered in this book effectively.

Download or read book Microsoft Azure Essentials Azure Machine Learning written by Jeff Barnes and published by Microsoft Press. This book was released on 2015-04-25 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.

Download or read book Emerging Concepts in Technology Enhanced Language Teaching and Learning written by Zou, Bin and published by IGI Global. This book was released on 2022-01-21 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: For years, language teachers have increasingly been using technologies of all kinds, from computers to smartphones, to help their students learn. Current trends in TELTL (technology-enhanced language teaching and learning), such as artificial intelligence, virtual reality, augmented reality, gamification, and social networking, appear to represent major shifts in the digital language learning landscape. However, various applications of technology to mediate language learning may be informed by reflecting not only on the present but perhaps more importantly on relevant insights from past research and practice. Emerging Concepts in Technology-Enhanced Language Teaching and Learning explores the recent development of the new technologies for language teaching and learning to gain insights into and synergy of the theories, pedagogies, technological design, and evaluation of TELTL environments for comprehending the trends and strategies of the new digital era as well as investigate the possibility of future TELTL research direction. The book includes trends shaped by contemporary issues such as the COVID-19 pandemic. Covering topics such as digital education tools, L2 learnings, and sentiment analysis, this book serves as an essential resource for researchers, language teachers, educational software developers, administrators, IT consultants, technologists, professors, pre-service teachers, academicians, and students.

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Download or read book The Large Intestine written by Sidney F. Phillips and published by Lippincott Williams & Wilkins. This book was released on 1991 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Unveiling the Tumor Microenvironment by Machine Learning to Develop New Immunotherapeutic Strategies Volume I A written by Nan Zhang and published by Frontiers Media SA. This book was released on 2023-10-24 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tumor microenvironment (TME) plays a critical role in tumor proliferation, progression, and therapeutic responses. TME is a complex network of cancer cells, stromal cells, and, most importantly, infiltrating immune cells. Cancer cells regulate numerous biological functions through direct or indirect interaction with TME components. Emerging evidence suggests that TME crucially influences the response to both chemotherapy and immunotherapy. As scientific research has entered the big data era with the fast development of high-throughput sequencing technologies, machine learning has been gradually widely applied to extract important knowledge from big data bioinformatics. Thus, characterizing the TME landscape in cancer and identifying different immune-related TME phenotypes using machine learning-based bioinformatics analyses, in vitro experiments, and in vivo experiments are of great interest and significance.

Download or read book NIKE Neuroendocrine Tumors Innovation in Knowledge and Education written by Antongiulio Faggiano and published by Frontiers Media SA. This book was released on 2021-09-09 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book AI IA 2017 Advances in Artificial Intelligence written by Floriana Esposito and published by Springer. This book was released on 2017-11-03 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2017, held in Bari, Italy, in November 2017. The 37 full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on applications of AI; natural language processing; knowledge representation and reasoning; knowledge engineering, ontologies and the semantic web; machinelearning; philosophical foundations, metacognitive modeling and ethics; and planning and scheduling.

Download or read book Microplastic Occurrence Fate Impact and Remediation written by Chongqing Wang and published by Springer Nature. This book was released on 2023-08-11 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microplastics and nanoplastics have been recently found in most environmental media and in living organisms, thus representing a serious health concern of yet poorly known adverse consequences. This book summarizes recent findings on the sources, behavior, transformation, toxicity and remediation of microplastics, with focus on soils, water, wastewater, air, soils, plants and corals. Advanced methods for sampling, characterization, removal and degradation of microplastics.

Download or read book Internet of Things Based Machine Learning in Healthcare written by Prasenjit Dey and published by CRC Press. This book was released on 2024-06-10 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems. Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services Discusses unsupervised genetic algorithm-based automatic heart disease prediction Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.

Download or read book Coloured Petri Nets written by Kurt Jensen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contents of this volume are application oriented. The volume contains a de tailed presentation of 19 applications of CP-nets, covering a broad range of ap plication areas. Most of the projects have been carried out in an industrial set ting. The volume presents the most important ideas and experiences from the projects, in a way which is useful also for readers who do not yet have personal experience with the construction and analysis of large CPN models. The volume demonstrates the feasibility of using CP-nets and the CPN tools for industrial projects. The presentation of the projects is based upon material provided by the per sons who have accomplished the individual projects. At the beginning of each chapter, we list their names and we say where the original material has been published. The original material often contains more elaborate information, e.g., about details of the modelled system and related work. I have edited the material provided by the original authors. I have modified some of the CP-nets, e.g., to improve the layout and use more mnemonic names. In some cases, I have also changed a few net components, e.g., merged two tran sitions or introduced a Standard ML function for operations that are used in many arc expressions. These modifications make the CP-nets more appropriate as study material, but they do not change the essential behaviour of the CPN models.

Download or read book Machine learning and deep learning applications in pathogenic microbiome research written by Gang Ye and published by Frontiers Media SA. This book was released on 2024-09-30 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: The pathogenic microbiome is the community of microorganisms that live in humans or animals and cause disease. These microorganisms include bacteria, viruses, fungi, protozoa, etc. They usually live in the host's skin, mouth, intestinal tract, genitourinary tract, etc. Normally, there is a state of equilibrium between the host and these microorganisms, but when this equilibrium is disturbed, these microorganisms become the pathogenic microbiome and cause disease. To advance the field of microbiome research, artificial intelligence methods, especially machine learning and deep learning, have recently been used as important tools due to their powerful predictive and informative potential. Classical machine learning algorithms such as linear regression, random forests, support vector machines, etc. perform well on microbiome data. However, as algorithms have been iteratively updated, these models have long been relegated to the basics. Linear regression models are now more often used to interpret these models more intuitively by using the output of other models as input. Deep learning is a branch of machine learning that involves a large number of neural network structures. Deep learning relies on neurons whose role is to transform the input and propagate it forward to the next neuron. Deep learning is currently being used with spectacular success in areas such as image recognition, text processing and automatic translation. As a result, a growing number of researchers are attempting to apply deep learning techniques to biomedical data analysis. Although there are still challenges in practical applications, such as model interpretability, data availability, model evaluation and selection, machine learning and deep learning are very promising tools in pathogenic microbiome research. This Research Topic, therefore, aims to contribute to the latest advances in machine learning, especially deep learning, and to explore new applications of related techniques in pathogenic microbiome research, trying to find relationships between microbiome and human health as well as the environment by studying high-throughput sequencing data of microbes, laying the foundation for further applications for subsequent treatment or forensic identification. We welcome submissions of Original Research, Brief Research Report, Review, Mini-Review, Methods, Perspective and Opinion articles that focus on, but are not limited to, the utilization of machine learning and deep learning to address the following subtopics. 1. Classification and identification of pathogenic microorganisms 2. Virulence prediction of pathogenic microorganisms 3. Antimicrobial resistance prediction of pathogenic microorganisms 4. Population structure and epidemiology of pathogenic microorganisms-related diseases 5. Immunological studies of pathogenic microorganisms 6. Drug target prediction for pathogenic microorganisms-related diseases

Download or read book Autoimmune Blistering Diseases written by Cezary Kowalewski and published by Frontiers Media SA. This book was released on 2020-09-08 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.