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Machine Learning Applications - - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning Applications - - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning Applications Practical resource on the importance of Machine Learning and Deep Learning applications in various technologies and real-world situations Machine Learning Applications discusses methodological advancements of machine learning and deep learning, presents applications in image processing, including face and vehicle detection, image classification, object detection, image segmentation, and delivers real-world applications in healthcare to identify diseases and diagnosis, such as creating smart health records and medical imaging diagnosis, and provides real-world examples, case studies, use cases, and techniques to enable the reader’s active learning. Composed of 13 chapters, this book also introduces real-world applications of machine and deep learning in blockchain technology, cyber security, and climate change. An explanation of AI and robotic applications in mechanical design is also discussed, including robot-assisted surgeries, security, and space exploration. The book describes the importance of each subject area and detail why they are so important to us from a societal and human perspective. Edited by two highly qualified academics and contributed to by established thought leaders in their respective fields, Machine Learning Applications includes information on: Content based medical image retrieval (CBMIR), covering face and vehicle detection, multi-resolution and multisource analysis, manifold and image processing, and morphological processing Smart medicine, including machine learning and artificial intelligence in medicine, risk identification, tailored interventions, and association rules AI and robotics application for transportation and infrastructure (e.g., autonomous cars and smart cities), along with global warming and climate change Identifying diseases and diagnosis, drug discovery and manufacturing, medical imaging diagnosis, personalized medicine, and smart health records With its practical approach to the subject, Machine Learning Applications is an ideal resource for professionals working with smart technologies such as machine and deep learning, AI, IoT, and other wireless communications; it is also highly suitable for professionals working in robotics, computer vision, cyber security and more.

DKK 923.00
3

Handbook of Human-Machine Systems - Bog af Fortino - Hardback

Machine Learning for iOS Developers - Abhishek Mishra - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning for iOS Developers - Abhishek Mishra - Bog - John Wiley & Sons Inc - Plusbog.dk

Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner! Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple’s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications. Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book’s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models—both pre-trained and user-built—with Apple’s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers: Understand the theoretical concepts and practical applications of machine learning used in predictive data analyticsBuild, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streamingDevelop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS)Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.

DKK 299.00
3

Machine Learning Upgrade - Caleb Kaiser - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning Upgrade - Caleb Kaiser - Bog - John Wiley & Sons Inc - Plusbog.dk

A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end system—not just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn't been codified yet, enabling you to forge the future using emerging best practices. Gain an understanding of the intersection between large language models and unstructured dataFollow the process of building an LLM-powered application while leveraging MLOps techniques such as data versioning and experiment trackingDiscover best practices for training, fine tuning, and evaluating LLMsIntegrate LLM applications within larger systems, monitor their performance, and retrain them on new data This book is indispensable for data professionals and business leaders looking to understand LLMs and the entire data science pipeline.

DKK 298.00
3

Machine Learning - Steven W. Knox - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning - Steven W. Knox - Bog - John Wiley & Sons Inc - Plusbog.dk

AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONSPROSE Award Finalist 2019 Association of American Publishers Award for Professional and Scholarly Excellence Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author—an expert in the field—presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection— essential elements of most applied projects. This important resource: - - Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods - - Presents R source code which shows how to apply and interpret many of the techniques covered - - Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions - - Contains useful information for effectively communicating with clients - A volume in the popular Wiley Series in Probability and Statistics, Machine Learning : a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning. STEVEN W. KNOX holds a Ph.D. in Mathematics from the University of Illinois and an M.S. in Statistics from Carnegie Mellon University. He has over twenty years’ experience in using Machine Learning, Statistics, and Mathematics to solve real-world problems. He currently serves as Technical Director of Mathematics Research and Senior Advocate for Data Science at the National Security Agency.

DKK 759.00
3

Machine Learning Theory and Applications - Xavier Vasques - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning Theory and Applications - Xavier Vasques - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning Theory and Applications Enables readers to understand mathematical concepts behind data engineering and machine learning algorithms and apply them using open-source Python libraries Machine Learning Theory and Applications delves into the realm of machine learning and deep learning, exploring their practical applications by comprehending mathematical concepts and implementing them in real-world scenarios using Python and renowned open-source libraries. This comprehensive guide covers a wide range of topics, including data preparation, feature engineering techniques, commonly utilized machine learning algorithms like support vector machines and neural networks, as well as generative AI and foundation models. To facilitate the creation of machine learning pipelines, a dedicated open-source framework named hephAIstos has been developed exclusively for this book. Moreover, the text explores the fascinating domain of quantum machine learning and offers insights on executing machine learning applications across diverse hardware technologies such as CPUs, GPUs, and QPUs. Finally, the book explains how to deploy trained models through containerized applications using Kubernetes and OpenShift, as well as their integration through machine learning operations (MLOps). Additional topics covered in Machine Learning Theory and Applications include: Current use cases of AI, including making predictions, recognizing images and speech, performing medical diagnoses, creating intelligent supply chains, natural language processing, and much moreClassical and quantum machine learning algorithms such as quantum-enhanced Support Vector Machines (QSVMs), QSVM multiclass classification, quantum neural networks, and quantum generative adversarial networks (qGANs)Different ways to manipulate data, such as handling missing data, analyzing categorical data, or processing time-related dataFeature rescaling, extraction, and selection, and how to put your trained models to life and production through containerized applicationsMachine Learning Theory and Applications is an essential resource for data scientists, engineers, and IT specialists and architects, as well as students in computer science, mathematics, and bioinformatics. The reader is expected to understand basic Python programming and libraries such as NumPy or Pandas and basic mathematical concepts, especially linear algebra.

DKK 693.00
3

Money Machine - W Shan - Bog - John Wiley & Sons Inc - Plusbog.dk

Money Machine - W Shan - Bog - John Wiley & Sons Inc - Plusbog.dk

An extraordinary tale of an American firm’s astounding success in China In Money Machine: A Trailblazing American Venture in China, Weijian Shan delivers a compelling account of one of the most significant deals in private equity history: the first and only foreign acquisition of control of a Chinese national bank. Money Machine is the fascinating inside story of the transaction as told by the man who led it, from the intrigues of dealmaking to the complex and uncharted process of securing control by a foreign investor of a Chinese nationwide financial institution, a feat that had never before been attempted, nor has it been repeated. Shan also describes the astonishingly successful turnaround of the institution under the control of the American firm: the clash of cultures, the growth to strength and profitability, and ultimately, the extraordinarily profitable exit from the investment. In the process, he reveals new insights into how finance operates in China’s capital system and how private equity firms can add real value to companies. Readers will also find: A peek behind the curtain of a process usually shrouded in secrecy: private equity dealmaking and moneymakingThe complex negotiations between American private equity executives and Chinese regulators to implement a series of unprecedented changesThe riveting details of the challenges that had to be overcome to return the bank to growth and profitabilityAn exceptional firsthand account of truly singular deal-making and money-making, Money Machine will be of interest to investment bankers, investors, financial analysts and anyone who appreciates a suspenseful, true-life story.

DKK 259.00
3

Fly Fishing For Dummies - Peter Kaminsky - Bog - John Wiley & Sons Inc - Plusbog.dk

Fly Fishing For Dummies - Peter Kaminsky - Bog - John Wiley & Sons Inc - Plusbog.dk

Hook up with the fly-fishing guide that’s a keeper Some say successful fly fishing requires supreme athleticism, a surgeon’s delicate touch, and the serene spirit of a Zen master. But forget the hype: The updated edition of Fly Fishing for Dummies shows that all you need to get the hang of this enjoyable sport are the right tools, a disciplined technique, and a positive attitude. Whether you’re an old salt or dipping your toes in for the first time, you’ll find everything you need to learn, improve, and keep your casting sharp and fresh! Longtime fishing writer Peter Kaminsky wades right in, taking you from choosing a rod and tying flies all the way through to staying dry with the right wardrobe and cooking up a delicious catch. You’ll also find out how you can get by with just 20 flies, a half dozen casts, and three knots. And, if you want to plunge deeper into the sport, he suggests some bucket-list destination rivers and streams to keep you agreeably hooked and learning for life—proving that the father of fishing writers Izaak Walton was right when, three centuries ago, he said: “No life is so pleasant and happy as that of a well-governed angler.” Study your quarry—from rainbow trout to fashionable “glamour” fishGet the best rod, reel, and gear for success—including the smartest techKnow where to fish (land or sea) and how to read the waterFollow visual examples to sharpen your casting Whatever your fly-fishing aims or skill level, the proven advice and 150+ illustrations in this friendly guide are your path to a lifetime of happy and productive trips: Don’t let it be the one that got away!

DKK 167.00
3

Machine Learning For Dummies - Bog af John Paul Mueller - Paperback

Machine Design with CAD and Optimization - Bog af Sayed M. (Cairo University Metwalli - Hardback

Python Machine Learning - Wei Meng Lee - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning in Chemical Safety and Health - Fundamentals with Applications - Bog af Q Wang - Hardback

Machine Learning Algorithms for Signal and Image Processing - Bog af SL Tripathi - Hardback

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide - Mona Mona - Bog - John Wiley & Sons Inc - Plusbog.dk

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide - Mona Mona - Bog - John Wiley & Sons Inc - Plusbog.dk

Expert, guidance for the Google Cloud Machine Learning certification exam In Google Cloud Certified Professional Machine Learning Study Guide, a team of accomplished artificial intelligence (AI) and machine learning (ML) specialists delivers an expert roadmap to AI and ML on the Google Cloud Platform based on new exam curriculum. With Sybex, you’ll prepare faster and smarter for the Google Cloud Certified Professional Machine Learning Engineer exam and get ready to hit the ground running on your first day at your new job as an ML engineer. The book walks readers through the machine learning process from start to finish, starting with data, feature engineering, model training, and deployment on Google Cloud. It also discusses best practices on when to pick a custom model vs AutoML or pretrained models with Vertex AI platform. All technologies such as Tensorflow, Kubeflow, and Vertex AI are presented by way of real-world scenarios to help you apply the theory to practical examples and show you how IT professionals design, build, and operate secure ML cloud environments. The book also shows you how to: Frame ML problems and architect ML solutions from scratchBanish test anxiety by verifying and checking your progress with built-in self-assessments and other practical toolsUse the Sybex online practice environment, complete with practice questions and explanations, a glossary, objective maps, and flash cardsA can’t-miss resource for everyone preparing for the Google Cloud Certified Professional Machine Learning certification exam, or for a new career in ML powered by the Google Cloud Platform, this Sybex Study Guide has everything you need to take the next step in your career.

DKK 494.00
3

Machine Learning - Jason Bell - Bog - John Wiley & Sons Inc - Plusbog.dk

Machine Learning - Jason Bell - Bog - John Wiley & Sons Inc - Plusbog.dk

Dig deep into the data with a hands-on guide to machine learning with updated examples and more! Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to: Learn the languages of machine learning including Hadoop, Mahout, and WekaUnderstand decision trees, Bayesian networks, and artificial neural networksImplement Association Rule, Real Time, and Batch learningDevelop a strategic plan for safe, effective, and efficient machine learning By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper.

DKK 322.00
1