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Who Raises the Sun? - T. P. Theyson - Bog - Moon Dust Press - Plusbog.dk

Who Raises the Sun? - T. P. Theyson - Bog - Moon Dust Press - Plusbog.dk

Have you ever asked yourself, Who raises the sun? Explore an assortment of deities from around the world given the important job of lighting our world every day in this exciting and intricately illustrated picture book from author T. P. Theyson. As readers are introduced to the different gods and goddesses who lift the sun into the sky each day and consider the divine debate over such an important job, they’ll be left with the sense that cooperation, teamwork, and acceptance all go into making our world a brighter place to live. Featuring stunningly detailed illustrations showing each deity moving the sun farther and farther into the sky, Who Raises the Sun? acquaints children ages three to eight years old with a unique and lesser-explored subject in world mythology. Deities included in the main text include: So’l, Unetlanvhi, Apollo, Surya, Wurpuranili, and Aurora, with more gods and goddesses included in an appendix following the story. To ensure authenticity and respect to the ancient myths and folklore on which this story is based, members of represented communities were consulted.

DKK 189.00
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Beginning Machine Learning in iOS - Mohit Thakkar - Bog - APress - Plusbog.dk

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

Implement machine learning models in your iOS applications. This short work begins by reviewing the primary principals of machine learning and then moves on to discussing more advanced topics, such as CoreML, the framework used to enable machine learning tasks in Apple products. Many applications on iPhone use machine learning: Siri to serve voice-based requests, the Photos app for facial recognition, and Facebook to suggest which people that might be in a photo. You''ll review how these types of machine learning tasks are implemented and performed so that you can use them in your own apps. Beginning Machine Learning in iOS is your guide to putting machine learning to work in your iOS applications. What You''ll Learn - Understand the CoreML components - Train custom models - Implement GPU processing for better computation efficiency - Enable machine learning in your application Who This Book Is For Novice developers and programmers who wish to implement machine learning in their iOS applications and those who want to learn the fundamentals about machine learning.

DKK 264.00
1

MATLAB Machine Learning Recipes - Michael Paluszek - Bog - APress - Plusbog.dk

MATLAB Machine Learning Recipes - Michael Paluszek - Bog - APress - Plusbog.dk

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What you''ll learn: - How to write code for machine learning, adaptive control and estimation using MATLAB - How these three areas complement each other - How these three areas are needed for robust machine learning applications - How to use MATLAB graphics and visualization tools for machine learning - How to code real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.

DKK 375.00
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Machine Learners - Adrian (professor Mackenzie - Bog - MIT Press Ltd - Plusbog.dk

Machine Learners - Adrian (professor Mackenzie - Bog - MIT Press Ltd - Plusbog.dk

If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought? Machine learning—programming computers to learn from data—has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking. Mackenzie focuses on machine learners—either humans and machines or human-machine relations—situated among settings, data, and devices. The settings range from fMRI to Facebook; the data anything from cat images to DNA sequences; the devices include neural networks, support vector machines, and decision trees. He examines specific learning algorithms—writing code and writing about code—and develops an archaeology of operations that, following Foucault, views machine learning as a form of knowledge production and a strategy of power. Exploring layers of abstraction, data infrastructures, coding practices, diagrams, mathematical formalisms, and the social organization of machine learning, Mackenzie traces the mostly invisible architecture of one of the central zones of contemporary technological cultures. Mackenzie''s account of machine learning locates places in which a sense of agency can take root. His archaeology of the operational formation of machine learning does not unearth the footprint of a strategic monolith but reveals the local tributaries of force that feed into the generalization and plurality of the field.

DKK 333.00
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Machine Learning Systems - Jeff Smith - Bog - Manning Publications - Plusbog.dk

Machine Learning Systems - Jeff Smith - Bog - Manning Publications - Plusbog.dk

Summary Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. Foreword by Sean Owen, Director of Data Science, Cloudera Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology If you’re building machine learning models to be used on a small scale, you don't need this book. But if you're a developer building a production-grade ML application that needs quick response times, reliability, and good user experience, this is the book for you. It collects principles and practices of machine learning systems that are dramatically easier to run and maintain, and that are reliably better for users. About the Book Machine Learning Systems: Designs that scale teaches you to design and implement production-ready ML systems. You'll learn the principles of reactive design as you build pipelines with Spark, create highly scalable services with Akka, and use powerful machine learning libraries like MLib on massive datasets. The examples use the Scala language, but the same ideas and tools work in Java, as well. What's Inside - - Working with Spark, MLlib, and Akka - - Reactive design patterns - - Monitoring and maintaining a large-scale system - - Futures, actors, and supervision - About the Reader Readers need intermediate skills in Java or Scala. No prior machine learning experience is assumed. About the Author Jeff Smith builds powerful machine learning systems. For the past decade, he has been working on building data science applications, teams, and companies as part of various teams in New York, San Francisco, and Hong Kong. He blogs (https: //medium.com/@jeffksmithjr), tweets (@jeffksmithjr), and speaks (www.jeffsmith.tech/speaking) about various aspects of building real-world machine learning systems. Table of Contents PART 1 - FUNDAMENTALS OF REACTIVE MACHINE LEARNING 1) 1) Learning reactive machine learning 1) 1) Using reactive tools 1) PART 2 - BUILDING A REACTIVE MACHINE LEARNING SYSTEM 1) 1) Collecting data 1) 1) Generating features 1) 1) Learning models 1) 1) Evaluating models 1) 1) Publishing models 1) 1) Responding 1) PART 3 - OPERATING A MACHINE LEARNING SYSTEM 1) 1) Delivering 1) 1) Evolving intelligence 1)

DKK 370.00
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Python Machine Learning - Wei Meng Lee - Bog - John Wiley & Sons Inc - Plusbog.dk

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

Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs decreasing at the same time, there is no better time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. However, machine learning is not for the faint of heart—it requires a good foundation in statistics, as well as programming knowledge. Python Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. Readers will get started by following fundamental topics such as an introduction to Machine Learning and Data Science. For each learning algorithm, readers will use a real-life scenario to show how Python is used to solve the problem at hand. • Python data science—manipulating data and data visualization • Data cleansing • Understanding Machine learning algorithms • Supervised learning algorithms • Unsupervised learning algorithms • Deploying machine learning models Python Machine Learning is essential reading for students, developers, or anyone with a keen interest in taking their coding skills to the next level.

DKK 266.00
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JESPER JUST – THE GARDEN IN THE MACHINE - Jesper Just - Bog - Roulette Russe - Plusbog.dk

JESPER JUST – THE GARDEN IN THE MACHINE - Jesper Just - Bog - Roulette Russe - Plusbog.dk

The Garden in the Machine is a groundbreaking total installation by renowned artist Jesper Just that explores the intricate relationship between natural and digitally produced environments. Set against the striking façade of Filmby Aarhus, this immersive work transforms the building into a canvas, projecting an interactive image sequence of a slowly rotating forest from sunset until midnight. At the heart of this installation is a solitary Scots Pine, equipped with sensors that continuously register its photosynthetic processes, dictating the film’s flow in real-time. Spanning an impressive 1,400 square meters and utilising 13.2 kilometres of LED strips, The Garden in the Machine stands as one of the largest video installations in the world. This book offers an in-depth exploration of Just’s artistic vision, technical ingenuity, and the profound questions his work raises about reality, perception, and the intertwining of the organic and the artificial.

DKK 335.00
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Introducing Machine Learning - Francesco Esposito - Bog - Pearson Education (US) - Plusbog.dk

Introducing Machine Learning - Francesco Esposito - Bog - Pearson Education (US) - Plusbog.dk

Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. · 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you · Explore what’s known about how humans learn and how intelligent software is built · Discover which problems machine learning can address · Understand the machine learning pipeline: the steps leading to a deliverable model · Use AutoML to automatically select the best pipeline for any problem and dataset · Master ML.NET, implement its pipeline, and apply its tasks and algorithms · Explore the mathematical foundations of machine learning · Make predictions, improve decision-making, and apply probabilistic methods · Group data via classification and clustering · Learn the fundamentals of deep learning, including neural network design · Leverage AI cloud services to build better real-world solutions faster About This Book · For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills · Includes examples of machine learning coding scenarios built using the ML.NET library

DKK 278.00
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Discovering Machine Knitting - Kandy Diamond - Bog - The Crowood Press Ltd - Plusbog.dk

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

The ultimate guide to machine knitting. This book has been designed to help you demystify machine knitting. Perfect for beginners, it starts with how the machine works and how stitches are formed, all the way through to shaping garment panels to your desired size and fit. Each chapter focuses on different skills that build throughout the book, with lots of projects so you can put the skills into practice and make some knits for yourself. Designer Profiles at the end of each chapter showcase the work of professional machine knitters to provide context, inspiration and celebrate the huge potential for creativity in machine knitting. From troubleshooting and looking after the machine to using more advanced techniques such as intarsia and shaping, this book will help you fall in love with your knitting machine. If you work through the step-by-step instructions and projects in this book, by the end of it you will be designing and knitting your own garments!

DKK 182.00
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Machine Learning with TensorFlow - Nishant Shukla - Bog - Manning Publications - Plusbog.dk

Machine Learning with TensorFlow - Nishant Shukla - Bog - Manning Publications - Plusbog.dk

DESCRIPTION Being able to make near-real-time decisions is becoming increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you''re just starting out in the data science field, how do you get started creating machine learning applications? The answer is TensorFlow, a new open source machine learning library from Google. The TensorFlow library can take your high level designs and turn them into the low level mathematical operations required by machine learning algorithms. Machine Learning with TensorFlow teaches readers about machine learning algorithms and how to implement solutions with TensorFlow. It starts with an overview of machine learning concepts and moves on to the essentials needed to begin using TensorFlow. Each chapter zooms into a prominent example of machine learning. Readers can cover them all to master the basics or skip around to cater to their needs. By the end of this book, readers will be able to solve classification, clustering, regression, and prediction problems in the real world. KEY FEATURES • Lots of diagrams, code examples, and exercises • Solves real-world problems with TensorFlow • Uses well-studied neural network architectures • Presents code that can be used for the readers’ own applications AUDIENCE This book is for programmers who have some experience with Python and linear algebra concepts like vectors and matrices. No experience with machine learning is necessary. ABOUT THE TECHNOLOGY Google open-sourced their machine learning framework called TensorFlow in late 2015 under the Apache 2.0 license. Before that, it was used proprietarily by Google in its speech recognition, Search, Photos, and Gmail, among other applications. TensorFlow is one the most popular machine learning libraries.

DKK 349.00
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The Omen Machine - Terry Goodkind - Bog - HarperCollins Publishers - Plusbog.dk

The Omen Machine - Terry Goodkind - Bog - HarperCollins Publishers - Plusbog.dk

A new Kahlan and Richard fantasy novel from bestselling author, Terry Goodkind.An accident leads to the discovery of a mysterious machine that has rested hidden deep underground for countless millennia. The machine awakens to begin issuing a series of increasingly alarming, if minor, omens. The omens turn out to be astonishingly accurate, and ever more ominous.As Zedd tries to figure out how to destroy the sinister device, the machine issues a cataclysmic omen involving Richard and Kahlan, foretelling an impending event beyond anyone’s ability to stop. As catastrophe approaches, the machine then reveals that it is within its power to withdraw the omen . . . In exchange for an impossible demand.

DKK 156.00
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Machine Embroidered Art - Alison Holt - Bog - Search Press Ltd - Plusbog.dk

Machine Embroidered Art - Alison Holt - Bog - Search Press Ltd - Plusbog.dk

This is a must-have instructional and inspirational book for anyone interested in free-motion embroidery. Drawing on new material, as well as that previously published as The Beginner’s Guide to Machine Embroidered Flowers , The Beginner’s Guide to Machine Embroidered Landscapes, Machine Embroidered Seascapes and Machine Embroidered Woodlands , this book provides a showcase of Alison Holt’s exquisite machine embroideries. Learn how to create beautiful machine-embroidered pictures of all aspects of the landscape, from formal gardens and flowers to romantic seascapes, landscapes and woodlands using various combinations of just two simple machine stitches. Information on silk painting and colour mixing is also included. All the techniques are broken down into clear, step-by-step instructions, with numerous helpful photographs and a great range of inspirational pieces. Alison ''paints'' her threads on to hand-coloured backgrounds, blending her stitches and achieving stunning results. This book covers everything, including the materials required; how to compose a picture from photographs that have inspired you; achieving perspective; light and shade; painting backgrounds; and all the basic stitch techniques you need to know. There are stunning step-by-step projects so that the reader can put into practise his or her newly-acquired skills.

DKK 202.00
1

The Calf - Leif Høghaug - Bog - FUM D'ESTAMPA PRESS - Plusbog.dk

The Calf - Leif Høghaug - Bog - FUM D'ESTAMPA PRESS - Plusbog.dk

On violence, crime, guilt and atonement. We meet our narrator in an underground office where he sharpens pencils, shreds paper, makes coffee for the other employees and thinks over and over about a late night that he has been trying to forget for a long time. In between the meaningless work, he manages to scratch down some names and phrases, and conjures up a dream from 1980s Hadeland. In this saga, Hadeland is a shadow home where spooks, ghosts, angels and robot-like creatures are just as natural as animals and flesh and blood humans. But what happened that late summer night? What is it that the narrator has tried to forget? And who is this Calf, who was “killed to death”? Our narrator takes readers in circles through different events, times and places; a whirlwind in which the calf and other characters are like prisoners in a tornado from Dante’s Inferno. The Calf is a peasant story, a western novel, a dream quatrain, an adventure, science fiction and a black comedy about violence, crime, guilt and atonement.

DKK 159.00
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Machine Learning for Managers - Paul (university Of Auckland Geertsema - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning for Managers - Paul (university Of Auckland Geertsema - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math. The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization. This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.

DKK 363.00
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Human and Machine Learning - - Bog - Springer International Publishing AG - Plusbog.dk

Human and Machine Learning - - Bog - Springer International Publishing AG - Plusbog.dk

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of "black-box" in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.

DKK 158.00
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