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Coffee & Health - Gerard Debry - Bog - John Libbey Eurotext - Plusbog.dk

Coffee & Health - Gerard Debry - Bog - John Libbey Eurotext - Plusbog.dk

This monograph is an exhaustive survey of all the health effects, beneficial or otherwise, of coffee. It starts with a study of the cultivation, consumption and composition of coffee, then moves on to analyse the effects of coffee consumption, system by system: physiological properties, clinical consequences, received opinions and proven facts. A book that will interest nutritionists, general practitioners and the simply curious.

DKK 544.00
1

Machine Learning Applications Using Python - Puneet Mathur - Bog - APress - Plusbog.dk

Machine Learning Applications Using Python - Puneet Mathur - Bog - APress - Plusbog.dk

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you''ll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You''ll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. What You Will Learn - Discover applied machine learning processes and principles - Implement machine learning in areas of healthcare, finance, and retail - Avoid the pitfalls of implementing applied machine learning - Build Python machine learning examples in the three subject areas Who This Book Is For Data scientists and machine learning professionals.

DKK 604.00
1

Much Ado Over Coffee - Bhaswati Bhattacharya - Bog - Taylor & Francis Ltd - Plusbog.dk

Much Ado Over Coffee - Bhaswati Bhattacharya - Bog - Taylor & Francis Ltd - Plusbog.dk

Based on oral history, fiction, fascinating intellectual gossip, and records of the Coffee Board of India, this study is a multi-sited ethnography of the Indian Coffee House, possibly the world’s first coffee house chain. It offers a critical analysis of adda (informal meetings) of the educated middle class in Allahabad, Calcutta and Delhi. The coffee house became the new socio-intellectual nerve centre, replacing the neigbourhood tea shops, and creating an entirely different social space. This book will have line drawings and cartoons as well as archival photographs.

DKK 448.00
1

Coffee Culture - Catherine M. Tucker - Bog - Taylor & Francis Ltd - Plusbog.dk

Coffee Culture - Catherine M. Tucker - Bog - Taylor & Francis Ltd - Plusbog.dk

Coffee Culture: Local experiences, Global Connections explores coffee as (1) a major commodity that shapes the lives of millions of people; (2) a product with a dramatic history; (3) a beverage with multiple meanings and uses (energizer, comfort food, addiction, flavouring, and confection); (4) an inspiration for humor and cultural critique; (5) a crop that can help protect biodiversity yet also threaten the environment; (6) a health risk and a health food; and (7) a focus of alternative trade efforts. This book presents coffee as a commodity that ties the world together, from the coffee producers and pickers who tend the plantations in tropical nations, to the middlemen and processors, to the consumers who drink coffee without ever having to think about how the drink reached their hands.

DKK 403.00
1

The Human Factor in Machine Translation - - Bog - Taylor & Francis Ltd - Plusbog.dk

The Human Factor in Machine Translation - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine translation has become increasingly popular, especially with the introduction of neural machine translation in major online translation systems. However, despite the rapid advances in machine translation, the role of a human translator remains crucial. As illustrated by the chapters in this book, man-machine interaction is essential in machine translation, localisation, terminology management, and crowdsourcing translation. In fact, the importance of a human translator before, during, and after machine processing, cannot be overemphasised as human intervention is the best way to ensure the translation quality of machine translation. This volume explores the role of a human translator in machine translation from various perspectives, affording a comprehensive look at this topical research area. This book is essential reading for anyone involved in translation studies, machine translation or interested in translation technology.

DKK 468.00
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Machine Learning for Decision Makers - Patanjali Kashyap - Bog - APress - Plusbog.dk

Machine Learning for Decision Makers - Patanjali Kashyap - Bog - APress - Plusbog.dk

This new and updated edition takes you through the details of machine learning to give you an understanding of cognitive computing, IoT, big data, AI, quantum computing, and more. The book explains how machine learning techniques are used to solve fundamental and complex societal and industry problems. This second edition builds upon the foundation of the first book, revises all of the chapters, and updates the research, case studies, and practical examples to bring the book up to date with changes that have occurred in machine learning. A new chapter on quantum computers and machine learning is included to prepare you for future challenges. Insights for decision makers will help you understand machine learning and associated technologies and make efficient, reliable, smart, and efficient business decisions. All aspects of machine learning are covered, ranging from algorithms to industry applications. Wherever possible, required practical guidelines and best practices related to machine learning and associated technologies are discussed. Also covered in this edition are hot-button topics such as ChatGPT, superposition, quantum machine learning, and reinforcement learning from human feedback (RLHF) technology. Upon completing this book, you will understand machine learning, IoT, and cognitive computing and be prepared to cope with future challenges related to machine learning. What You Will LearnMaster the essentials of machine learning, AI, cloud, and the cognitive computing technology stackUnderstand business and enterprise decision-making using machine learningBecome familiar with machine learning best practicesGain knowledge of quantum computing and quantum machine learningWho This Book Is ForManagers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them

DKK 476.00
1

Quality Determinants In Coffee Production - - Bog - Springer Nature Switzerland AG - Plusbog.dk

Quality Determinants In Coffee Production - - Bog - Springer Nature Switzerland AG - Plusbog.dk

Quality Determinants In Coffee Production presents a comprehensive overview of the main determinants of coffee quality during processing. Authored by members of the Laboratory for Analysis and Research in Coffee at the Federal Institute of Espírito Santo, the chapters in this text explain how coffee quality can be affected through each step of the main processing methods. The first section explores the history of coffee processing, covering how the processes and techniques of sensorial analysis have developed. The second section covers the evolution of these techniques and how various complexities can affect their use, plus the statistical tools that are used to increase test accuracy. Another section focuses on the relationship between fruit microbiology and coffee quality, promoting an understanding of how yeasts, fungi and bacteria effect the quality of coffee during processing. Another section is dedicated to the biotechnological processes used in coffee production, including the applicability of induced and spontaneous routes from the manipulation of raw material, the relationship between wet processing and spontaneous fermentation and the construction of sensorial routes. A final section explores volatile coffee compounds and gas chromatography techniques, including chemical and sensory maps. The majority of the reference works published on coffee processing have a pragmatic approach covering production, harvesting, post-harvesting and marketing. This work goes beyond these subjects, covering the factors that impact quality and how they lead to either qualitative reduction or gains during processing. New technological and scientific indicators for the modification and the creation of sensory routes are extensively covered, as are the international protocols used in the sensorial analysis of coffee. With its broad approach, this text presents a multidisciplinary perspective connecting areas such as statistics, biochemistry, analytical chemistry and microbiology to the results of sensory analysis using different technologies and processes. A direct relationship between these factors is established in order to help researchers understand their combined effect on coffee quality during processing.

DKK 689.00
1

Machine Learning for Healthcare - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning for Healthcare - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: - A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.

DKK 459.00
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Functional Reverse Engineering of Machine Tools - - Bog - Taylor & Francis Ltd - Plusbog.dk

Functional Reverse Engineering of Machine Tools - - Bog - Taylor & Francis Ltd - Plusbog.dk

The purpose of this book is to develop capacity building in strategic and non-strategic machine tool technology. The book contains chapters on how to functionally reverse engineer strategic and non-strategic computer numerical control machinery. Numerous engineering areas, such as mechanical engineering, electrical engineering, control engineering, and computer hardware and software engineering, are covered. The book offers guidelines and covers design for machine tools, prototyping, augmented reality for machine tools, modern communication strategies, and enterprises of functional reverse engineering, along with case studies. Features - - Presents capacity building in machine tool development - - - Discusses engineering design for machine tools - - - Covers prototyping of strategic and non-strategic machine tools - - - Illustrates augmented reality for machine tools - - - Includes Internet of Things (IoT) for machine tools -

DKK 505.00
1

Distributed Machine Learning Patterns - Yuan Tang - Bog - Manning Publications - Plusbog.dk

Distributed Machine Learning Patterns - Yuan Tang - Bog - Manning Publications - Plusbog.dk

Practical patterns for scaling machine learning from your laptop to a distributed cluster. In Distributed Machine Learning Patterns you will learn how to: - - Apply distributed systems patterns to build scalable and reliable machine learning projects - - Construct machine learning pipelines with data ingestion, distributed training, model serving, and more - - Automate machine learning tasks with Kubernetes, TensorFlow, Kubeflow, and Argo Workflows - - Make trade offs between different patterns and approaches - - Manage and monitor machine learning workloads at scale - Scaling up models from standalone devices to large distributed clusters is one of the biggest challenges faced by modern machine learning practitioners. Distributed Machine Learning Patterns teaches you how to scale machine learning models from your laptop to large distributed clusters. In Distributed Machine Learning Patterns , you''ll learn how to apply established distributed systems patterns to machine learning projects, and explore new ML-specific patterns as well. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Real-world scenarios, hands-on projects, and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines Distributed Machine Learning Patterns teaches you how to scale machine learning models from your laptop to large distributed clusters. In it, you''ll learn how to apply established distributed systems patterns to machine learning projects, and explore new ML-specific patterns as well. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Real-world scenarios, hands-on projects, and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines. about the technology Scaling up models from standalone devices to large distributed clusters is one of the biggest challenges faced by modern machine learning practitioners. Distributing machine learning systems allow developers to handle extremely large datasets across multiple clusters, take advantage of automation tools, and benefit from hardware accelerations. In this book, Kubeflow co-chair Yuan Tang shares patterns, techniques, and experience gained from years spent building and managing cutting-edge distributed machine learning infrastructure. about the book Distributed Machine Learning Patterns is filled with practical patterns for running machine learning systems on distributed Kubernetes clusters in the cloud. Each pattern is designed to help solve common challenges faced when building distributed machine learning systems, including supporting distributed model training, handling unexpected failures, and dynamic model serving traffic. Real-world scenarios provide clear examples of how to apply each pattern, alongside the potential trade offs for each approach. Once you''ve mastered these cutting edge techniques, you''ll put them all into practice and finish up by building a comprehensive distributed machine learning system.

DKK 459.00
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Practical Machine Learning with Rust - Joydeep Bhattacharjee - Bog - APress - Plusbog.dk

Practical Machine Learning with Rust - Joydeep Bhattacharjee - Bog - APress - Plusbog.dk

Explore machine learning in Rust and learn about the intricacies of creating machine learning applications. This book begins by covering the important concepts of machine learning such as supervised, unsupervised, and reinforcement learning, and the basics of Rust. Further, you’ll dive into the more specific fields of machine learning, such as computer vision and natural language processing, and look at the Rust libraries that help create applications for those domains. We will also look at how to deploy these applications either on site or over the cloud. After reading Practical Machine Learning with Rust, you will have a solid understanding of creating high computation libraries using Rust. Armed with the knowledge of this amazing language, you will be able to create applications that are more performant, memory safe, and less resource heavy. What You Will LearnWrite machine learning algorithms in RustUse Rust libraries for different tasks in machine learningCreate concise Rust packages for your machine learning applicationsImplement NLP and computer vision in RustDeploy your code in the cloud and on bare metal servers Who This Book Is For Machine learning engineers and software engineers interested in building machine learning applications in Rust.

DKK 385.00
1

Machine Intelligence - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Intelligence - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machines are being systematically empowered to be interactive and intelligent in their operations, offerings. and outputs. There are pioneering Artificial Intelligence (AI) technologies and tools. Machine and Deep Learning (ML/DL) algorithms, along with their enabling frameworks, libraries, and specialized accelerators, find particularly useful applications in computer and machine vision, human machine interfaces (HMIs), and intelligent machines. Machines that can see and perceive can bring forth deeper and decisive acceleration, automation, and augmentation capabilities to businesses as well as people in their everyday assignments. Machine vision is becoming a reality because of advancements in the computer vision and device instrumentation spaces. Machines are increasingly software-defined. That is, vision-enabling software and hardware modules are being embedded in new-generation machines to be self-, surroundings, and situation-aware. Machine Intelligence: Computer Vision and Natural Language Processing emphasizes computer vision and natural language processing as drivers of advances in machine intelligence. The book examines these technologies from the algorithmic level to the applications level. It also examines the integrative technologies enabling intelligent applications in business and industry. Features: - Motion images object detection over voice using deep learning algorithms - Ubiquitous computing and augmented reality in HCI - Learning and reasoning in Artificial Intelligence - Economic sustainability, mindfulness, and diversity in the age of artificial intelligence and machine learning - Streaming analytics for healthcare and retail domains Covering established and emerging technologies in machine vision, the book focuses on recent and novel applications and discusses state-of-the-art technologies and tools.

DKK 630.00
1

Machine Learning with PySpark - Pramod Singh - Bog - APress - Plusbog.dk

Machine Learning with PySpark - Pramod Singh - Bog - APress - Plusbog.dk

Master the new features in PySpark 3.1 to develop data-driven, intelligent applications. This updated edition covers topics ranging from building scalable machine learning models, to natural language processing, to recommender systems. Machine Learning with PySpark, Second Edition begins with the fundamentals of Apache Spark, including the latest updates to the framework. Next, you will learn the full spectrum of traditional machine learning algorithm implementations, along with natural language processing and recommender systems. You''ll gain familiarity with the critical process of selecting machine learning algorithms, data ingestion, and data processing to solve business problems. You''ll see a demonstration of how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forests. You''ll also learn how to automate the steps using Spark pipelines, followed by unsupervised models such as K-means and hierarchical clustering. A section on Natural Language Processing (NLP) covers text processing, text mining, and embeddings for classification. This new edition also introduces Koalas in Spark and how to automate data workflow using Airflow and PySpark''s latest ML library. After completing this book, you will understand how to use PySpark''s machine learning library to build and train various machine learning models, along with related components such as data ingestion, processing and visualization to develop data-driven intelligent applications What you will learn: - Build a spectrum of supervised and unsupervised machine learning algorithms - Use PySpark''s machine learning library to implement machine learning and recommender systems - Leverage the new features in PySpark''s machine learning library - Understand data processing using Koalas in Spark - Handle issues around feature engineering, class balance, bias and variance, and cross validation to build optimally fit models Who This Book Is For Data science and machine learning professionals.

DKK 509.00
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Coffee Is Not Forever - Stuart Mccook - Bog - Ohio University Press - Plusbog.dk

Coffee Is Not Forever - Stuart Mccook - Bog - Ohio University Press - Plusbog.dk

The global coffee industry, which fuels the livelihoods of farmers, entrepreneurs, and consumers around the world, rests on fragile ecological foundations. In Coffee Is Not Forever, Stuart McCook explores the transnational story of this essential crop through a history of one of its most devastating diseases, the coffee leaf rust. He deftly synthesizes agricultural, social, and economic histories with plant genetics and plant pathology to investigate the increasing interdependence of the world’s coffee-producing zones. In the process, he illuminates the progress and prognosis of the challenges—especially climate change—that pose an existential threat to a crop that global consumers often take for granted. And finally, in putting a tropical plant disease at the forefront, he has crafted the first truly global environmental history of coffee, pushing its study and the discipline in bold new directions.

DKK 606.00
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Machine Learning Using R - Karthik Ramasubramanian - Bog - APress - Plusbog.dk

Machine Learning Using R - Karthik Ramasubramanian - Bog - APress - Plusbog.dk

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python if you are only comfortable with R. As in the first edition, the authors have kept the fine balance of theory and application of machine learning through various real-world use-cases which gives you a comprehensive collection of topics in machine learning. New chapters in this edition cover time series models and deep learning. What You''ll Learn - Understand machine learning algorithms using R - Master the process of building machine-learning models - Cover the theoretical foundations of machine-learning algorithms - See industry focused real-world use cases - Tackle time series modeling in R - Apply deep learning using Keras and TensorFlow in R Who This Book is For Data scientists, data science professionals, and researchers in academia who want to understand the nuances of machine-learning approaches/algorithms in practice using R.

DKK 519.00
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Antique Coffee Grinders - Michael White - Bog - Schiffer Publishing Ltd - Plusbog.dk

Antique Coffee Grinders - Michael White - Bog - Schiffer Publishing Ltd - Plusbog.dk

Even before its current zenith of popularity, coffee has been a favorite beverage worldwide for centuries. To prepare coffee beans for use, human ingenuity has created hundreds of versions of coffee grinders, and this book is devoted exclusively to them. With 600 quality color photographs, the authors direct a marvelous tour of the best and most sought after examples from around the world. Accurate information about the makers and the time and place of manufacture make this a valuable resource for collectors as well as a rich visual history of over 300 years of American and European coffee grinding devices. Each example is described with its current value. Joseph E. MacMillan, a leading authority on coffee grinders and author of the MacMillan Index, writes in his Foreword to this book, “Knowing the quality of these authors, I am confident that this book will be an asset to the serious collector and will be enjoyed by all of its readers for years to come.”

DKK 542.00
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Applied Machine Learning Using mlr3 in R - - Bog - Taylor & Francis Ltd - Plusbog.dk

Applied Machine Learning Using mlr3 in R - - Bog - Taylor & Francis Ltd - Plusbog.dk

mlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art machine learning capabilities in R. Applied Machine Learning Using mlr3 in R gives an overview of flexible and robust machine learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic machine learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of machine learning approaches to obtain peak performance; building machine learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with custom learners, measures, or pipeline components. Features: - In-depth coverage of the mlr3 ecosystem for users and developers - Explanation and illustration of basic and advanced machine learning concepts - Ready to use code samples that can be adapted by the user for their application - Convenient and expressive machine learning pipelining enabling advanced modelling - Coverage of topics that are often ignored in other machine learning books The book is primarily aimed at researchers, practitioners, and graduate students who use machine learning or who are interested in using it. It can be used as a textbook for an introductory or advanced machine learning class that uses R, as a reference for people who work with machine learning methods, and in industry for exploratory experiments in machine learning.

DKK 656.00
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Coffee Nation - Michelle Craig Mcdonald - Bog - University of Pennsylvania Press - Plusbog.dk

Coffee Nation - Michelle Craig Mcdonald - Bog - University of Pennsylvania Press - Plusbog.dk

Illuminates how coffee tied the economic future of the early United States to the wider Atlantic world Coffee is among the most common goods traded and consumed worldwide, and so omnipresent its popularity is often taken for granted. But even everyday habits have a history. When and why coffee become part of North American daily life is at the center of Coffee Nation. Using a wide range of archival, quantitative, and material evidence, Michelle Craig McDonald follows coffee from the slavery-based plantations of the Caribbean and South America, through the balance sheets of Atlantic world merchants, into the coffeehouses, stores, and homes of colonial North Americans, and ultimately to the growing import/export businesses of the early nineteenth-century United States that rebranded this exotic good as an American staple. The result is a sweeping history that explores how coffee shaped the lives of enslaved laborers and farmers, merchants and retailers, consumers and advertisers. Coffee Nation also challenges traditional interpretations of the American Revolution, as coffee's spectacular profitability in US markets and popularity on the new nation's tables by the mid-nineteenth century was the antithesis of independence. From its beginnings as a colonial commodity in the early eighteenth century, coffee's popularity soared to become a leading global economy by the 1830s. The United States dominated this growth, by importing ever-increasing amounts of the commodity for drinkers at home and developing a lucrative re-export trade to buyers overseas. But while income generated from coffee sales made up an expanding portion of US trade revenue, the market always depended on reliable access to a commodity that the nation could not grow for itself. By any measure, the coffee industry was a financial success story, but one that runs counter to the dominant narrative of national autonomy. Distribution, not production, lay at the heart of North America's coffee business, and its profitability and expansion relied on securing and maintaining ties first with the Caribbean and then Latin America.

DKK 416.00
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