3.700 resultater (0,40292 sekunder)

Vis alle filtre

Mærke

Vis alle

Butik

Pris (EUR)

Nulstil filter

Produkter
Fra
Butikker

Scientific Ocean Drilling - Ocean Studies Board - Bog - National Academies Press - Plusbog.dk

Scientific Ocean Drilling - Ocean Studies Board - Bog - National Academies Press - Plusbog.dk

Through direct exploration of the subseafloor, U.S.-supported scientific ocean drilling programs have significantly contributed to a broad range of scientific accomplishments in Earth science disciplines, shaping understanding of Earth systems and enabling new fields of inquiry. Scientific Ocean Drilling: Accomplishments and Challenges reviews the scientificaccomplishments of U.S.-supported scientific oceandrilling over the past four decades. The book evaluates how the programs (Deep Sea Drilling Project [DSDP], 1968-1983, Ocean Drilling Program [ODP], 1984-2003, and Integrated Ocean Drilling Program [IODP], 2003-2013) have shaped understanding of Earth systems and Earth history and assessed the role of scientific ocean drilling in enabling new fields of inquiry. This book also assesses the potential for transformative discoveries for the next proposed phase of scientific ocean drilling, which is scheduled to run from 2013 to 2023. The programs' technological innovations have played a strong role in these accomplishments. The science plan for the proposed 2013-2023 program presents a strong case for the continuation of scientific ocean drilling. Each of the plan's four themes identifies compelling challenges with potential for transformative science that could only be addressed through scientific ocean drilling, although some challenges appear to have greater potential than others. Prioritizing science plan challenges and integrating multiple objectives into single expeditions would help use resources more effectively, while encouraging technological innovations would continue to increase the potential for groundbreaking science. Table of ContentsFront MatterSummary1 Introduction to U.S. Scientific Ocean Drilling2 Scientific Accomplishments: Solid Earth Cycles3 Scientific Accomplishments: Fluids, Flow, and Life in the Subseafloor4 Scientific Accomplishments: Earth's Climate History5 Education, Outreach, and Capacity Building6 Assessment of Illuminating Earth's Past, Present, and Future: The International Ocean Discovery Program Science Plan for 2013-2023ReferencesA DSDP, ODP, and IODP Legs and ExpeditionsB Committee and Staff BiographiesC Workshop White PapersD Acronyms

DKK 305.00
1

Drilling through Hard Boards - Alexander Kluge - Bog - Seagull Books London Ltd - Plusbog.dk

Drilling through Hard Boards - Alexander Kluge - Bog - Seagull Books London Ltd - Plusbog.dk

Max Weber famously described politics as "a strong, slow drilling through hard boards with both passion and judgment." Taking this as his inspiration, Alexander Kluge brings readers yet another literary masterpiece. Drilling through Hard Boards is a kaleidoscopic meditation on the tools available to those who struggle for power. Weber's metaphorical drill certainly embodies intelligent tenacity as a precondition for political change. But what is a hammer in the business of politics, Kluge wonders, and what is a subtle touch? Eventually, we learn that all questions of politics lead to a single one: what is political in the first place? In the book, Kluge masterfully unspools more than one hundred vignettes, through which it becomes clear that the political is more often than not personal. Politics are everywhere in our everyday lives, so along with the stories of major political figures, we also find here the small, mostly unknown ones: Elfriede Eilers alongside Pericles, Chilean miners next to Napoleon, a three-month-old baby beside Alexander the Great. Drilling through Hard Boards is not just Kluge's newest fiction, it is a masterpiece of political thought.

DKK 220.00
1

The Earth's Magnetic Interior - - Bog - Springer - Plusbog.dk

The Earth's Magnetic Interior - - Bog - Springer - Plusbog.dk

This volume combines review and solicited contributions, related to scientific studies of Division I of IAGA presented at its Scientific Assembly in Sopron in 2009. The book is aimed at intermediate to advanced readers dealing with the Earth’s magnetic field generation, its historical records in rocks and geological formations - including links to geodynamics and magnetic dating, with magnetic carriers in earth materials, electromagnetic induction and conductivity studies of the Earth interior with environmental applications of rock magnetism and electromagnetism. The aim of the book is to provide an overview of recent advances and future challenges in these particular fields of research.

DKK 347.00
1

Progress and Priorities in Ocean Drilling: In Search of Earth's Past and Future - 2025–2035 Decadal Survey Of Ocean Sciences For The National Science

Progress and Priorities in Ocean Drilling: In Search of Earth's Past and Future - 2025–2035 Decadal Survey Of Ocean Sciences For The National Science

Research supported by scientific ocean drilling has fundamentally transformed our understanding of the planet with key contributions to the discovery and theory of plate tectonics; the formation and destruction of ocean crust; the reconstruction of extreme greenhouse and icehouse climates; the identification of major extinctions; and the discovery of a diverse community of microbes living deep ocean seafloor. With the retirement in 2024 of the JOIDES Resolution-- the U.S. dedicated drilling vessel for deep sea research and the workhorse for the international scientific ocean drilling community-- the scientific ocean drilling landscape will change. At this critical juncture, the National Science Foundation (NSF) is looking to identify the most urgent research questions that can only be answered with scientific ocean drilling and what infrastructure is needed to progress those priorities. This interim report that is the first part of a broader study of decadal survey of ocean science provides a broad perspective of future research and associated infrastructure needs. The report concludes that the rapid pace of climate change, related extreme events, sea level rise, changes in ocean currents, chemistry threatening ocean ecosystems, and devastating natural hazards are among the greatest challenges facing society. By coring the past to inform the future, U.S. based scientific ocean drilling research continues to have unique and essential roles in addressing these vital and urgent challenges. Table of ContentsFront MatterSummary1 Introduction2 A Primer on Scientific Ocean Drilling3 High-Priority Science Areas: Progress and Future Needs4 Needs for Accomplishing the Science PrioritiesReferencesAppendix A: Committee Statement of TaskAppendix B: Committee Meeting Agenda and Participant ListAppendix C: Committee Biographies

DKK 208.00
1

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
1

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
1

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
1

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
1

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
1

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
1

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
1