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Advanced Machine Learning - Avinash Sharma - Bog - BPB Publications - Plusbog.dk

Advanced Computing, Machine Learning, Robotics and Internet Technologies - - Bog - Springer International Publishing AG - Plusbog.dk

Advanced Computing, Machine Learning, Robotics and Internet Technologies - - Bog - Springer International Publishing AG - Plusbog.dk

Weighing Lives - John Broome - Bog - Oxford University Press - Plusbog.dk

Weighing Lives - John Broome - Bog - Oxford University Press - Plusbog.dk

We are often faced with choices that involve the weighing of people''s lives against each other, or the weighing of lives against other good things. These are choices both for individuals and for societies. A person who is terminally ill may have to choose between palliative care and more aggressive treatment, which will give her a longer life but at some cost in suffering. We have to choose between the convenience to ourselves of road and air travel, and the lives of the future people who will be killed by the global warming we cause, through violent weather, tropical disease, and heat waves. We also make choices that affect how many lives there will be in the future: as individuals we choose how many children to have, and societies choose tax policies that influence people''s choices about having children. These are all problems of weighing lives.How should we weigh lives? Weighing Lives develops a theoretical basis for answering this practical question. It extends the work and methods of Broome''s earlier book Weighing Goods to cover the questions of life and death.Difficult problems come up in the process. In particular, Weighing Lives tackles the well-recognized, awkward problems of the ethics of population. It carefully examines the common intuition that adding people to the population is ethically neutral - neither a good nor a bad thing - but eventually concludes this intuition cannot be fitted into a coherent theory of value. In the course of its argument, Weighing Lives examines many of the issues of contemporary moral theory: the nature of consequentialism and teleology; the transitivity, continuity, and vagueness of betterness; the quantitative conception of wellbeing; the notion of a life worth living; the badness of death; and others.This is a work of philosophy, but one of its distinctive features is that it adopts some of the precise methods of economic theory (without introducing complex mathematics). Not only philosophers, but also economists and political theorists concerned with the practical question of valuing life, should find the book''s conclusions highly significant to their work.

DKK 383.00
1

Weighing Lives - John Broome - Bog - Oxford University Press - Plusbog.dk

Weighing Lives - John Broome - Bog - Oxford University Press - Plusbog.dk

We are often faced with choices that involve the weighing of people''s lives against each other, or the weighing of lives against other good things. These are choices both for individuals and for societies. A person who is terminally ill may have to choose between palliative care and more aggressive treatment, which will give her a longer life but at some cost in suffering. We have to choose between the convenience to ourselves of road and air travel, and the lives of the future people who will be killed by the global warming we cause, through violent weather, tropical disease, and heat waves. We also make choices that affect how many lives there will be in the future: as individuals we choose how many children to have, and societies choose tax policies that influence people''s choices about having children. These are all problems of weighing lives.How should we weigh lives? Weighing Lives develops a theoretical basis for answering this practical question. It extends the work and methods of Broome''s earlier book Weighing Goods to cover the questions of life and death.Difficult problems come up in the process. In particular, Weighing Lives tackles the well-recognized, awkward problems of the ethics of population. It carefully examines the common intuition that adding people to the population is ethically neutral - neither a good nor a bad thing - but eventually concludes this intuition cannot be fitted into a coherent theory of value. In the course of its argument, Weighing Lives examines many of the issues of contemporary moral theory: the nature of consequentialism and teleology; the transitivity, continuity, and vagueness of betterness; the quantitative conception of wellbeing; the notion of a life worth living; the badness of death; and others.This is a work of philosophy, but one of its distinctive features is that it adopts some of the precise methods of economic theory (without introducing complex mathematics). Not only philosophers, but also economists and political theorists concerned with the practical question of valuing life, should find the book''s conclusions highly significant to their work.

DKK 1110.00
1

Weighing and Reasoning - - Bog - Oxford University Press - Plusbog.dk

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
1

Weighing Lives in War - - Bog - Oxford University Press - Plusbog.dk

Machine Learning for Tabular Data - Mark Ryan - Bog - Manning Publications - Plusbog.dk

Machine Learning - Jugal Kalita - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning - Jugal Kalita - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples. Features: - Provides an easy-to-read presentation of commonly used machine learning algorithms in a manner suitable for advanced undergraduate or beginning graduate students, and mathematically and/or programming-oriented individuals who want to learn machine learning on their own. Covers mathematical details of the machine learning algorithms discussed to ensure firm understanding, enabling further exploration Presents worked out suitable programming examples, thus ensuring conceptual, theoretical and practical understanding of the machine learning methods. This book is aimed primarily at introducing essential topics in Machine Learning to advanced undergraduates and beginning graduate students. The number of topics has been kept deliberately small so that it can all be covered in a semester or a quarter. The topics are covered in depth, within limits of what can be taught in a short period of time. Thus, the book can provide foundations that will empower a student to read advanced books and research papers.

DKK 468.00
1

Coverbal Synchrony in Human-Machine Interaction - - Bog - Taylor & Francis Ltd - Plusbog.dk

Coverbal Synchrony in Human-Machine Interaction - - Bog - Taylor & Francis Ltd - Plusbog.dk

Embodied conversational agents (ECA) and speech-based human–machine interfaces can together represent more advanced and more natural human–machine interaction. Fusion of both topics is a challenging agenda in research and production spheres. The important goal of human–machine interfaces is to provide content or functionality in the form of a dialog resembling face-to-face conversations. All natural interfaces strive to exploit and use different communication strategies that provide additional meaning to the content, whether they are human–machine interfaces for controlling an application or different ECA-based human–machine interfaces directly simulating face-to-face conversation. Coverbal Synchrony in Human-Machine Interaction presents state-of-the-art concepts of advanced environment-independent multimodal human–machine interfaces that can be used in different contexts, ranging from simple multimodal web-browsers (for example, multimodal content reader) to more complex multimodal human–machine interfaces for ambient intelligent environments (such as supportive environments for elderly and agent-guided household environments). They can also be used in different computing environments—from pervasive computing to desktop environments. Within these concepts, the contributors discuss several communication strategies, used to provide different aspects of human–machine interaction.

DKK 643.00
1

American Milling Machine Builders 1820-1920 - Kenneth L. Cope - Bog - Astragal Press - Plusbog.dk

Beginning Machine Learning in iOS - Mohit Thakkar - Bog - APress - Plusbog.dk

Applications of Optimization and Machine Learning in Image Processing and IoT - - Bog - Taylor & Francis Ltd - Plusbog.dk

Signal Processing and Machine Learning with Applications - Michael M. Richter - Bog - Springer International Publishing AG - Plusbog.dk

Machine Learning - Zhi Hua Zhou - Bog - Springer Verlag, Singapore - Plusbog.dk

Advanced Manufacturing Methods - - Bog - Taylor & Francis Ltd - Plusbog.dk

Python Machine Learning By Example - Yuxi Liu - Bog - Packt Publishing Limited - Plusbog.dk

Python Machine Learning By Example - Yuxi Liu - Bog - Packt Publishing Limited - Plusbog.dk

Author Yuxi (Hayden) Liu teaches machine learning from the fundamentals to building NLP transformers and multimodal models with best practice tips and real-world examples using PyTorch, TensorFlow, scikit-learn, and pandasKey FeaturesDiscover new and updated content on NLP transformers, PyTorch, and computer vision modelingIncludes a dedicated chapter on best practices and additional best practice tips throughout the book to improve your ML solutionsImplement ML models, such as neural networks and linear and logistic regression, from scratchPurchase of the print or Kindle book includes a free PDF copyBook DescriptionThe fourth edition of Python Machine Learning By Example is a comprehensive guide for beginners and experienced machine learning practitioners who want to learn more advanced techniques, such as multimodal modeling. Written by experienced machine learning author and ex-Google machine learning engineer Yuxi (Hayden) Liu, this edition emphasizes best practices, providing invaluable insights for machine learning engineers, data scientists, and analysts. Explore advanced techniques, including two new chapters on natural language processing transformers with BERT and GPT, and multimodal computer vision models with PyTorch and Hugging Face. You’ll learn key modeling techniques using practical examples, such as predicting stock prices and creating an image search engine. This hands-on machine learning book navigates through complex challenges, bridging the gap between theoretical understanding and practical application. Elevate your machine learning and deep learning expertise, tackle intricate problems, and unlock the potential of advanced techniques in machine learning with this authoritative guide.What you will learnFollow machine learning best practices throughout data preparation and model developmentBuild and improve image classifiers using convolutional neural networks (CNNs) and transfer learningDevelop and fine-tune neural networks using TensorFlow and PyTorchAnalyze sequence data and make predictions using recurrent neural networks (RNNs), transformers, and CLIPBuild classifiers using support vector machines (SVMs) and boost performance with PCAAvoid overfitting using regularization, feature selection, and moreWho this book is forThis expanded fourth edition is ideal for data scientists, ML engineers, analysts, and students with Python programming knowledge. The real-world examples, best practices, and code prepare anyone undertaking their first serious ML project.

DKK 428.00
1

Discovering Machine Knitting - Kandy Diamond - Bog - The Crowood Press Ltd - Plusbog.dk