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Into the Deep
  • Language: en
  • Pages: 149

Into the Deep

Containing 97 percent of Earth's water supply, the ocean plays a huge role in regulating global temperatures, supporting plant and animal life, and contributing to the livelihoods of millions of people. But in spite of all this, the ocean remains drastically unexplored, and the details of its impact on human lives aren't fully understood. Scientists from around the world are realizing that to address issues plaguing the ocean, such as dead zones, coral bleaching, and climate change, we need to better understand this incredible, unique feature of our planet. With a range of impressive, cutting-edge technologies at their disposal, oceanographers have set out to measure, sample, and analyze at every turn. Every day, mysteries about the ocean are being solved, and every day, new questions come to light. The more scientists learn, the better they are able to answer these new questions. What lies in the deep? And who is at the forefront of these exciting discoveries? The scientists and research included in this book shed light on the most pressing issues currently facing oceanographers and point us in the right direction to solving these challenges.

A Century of Science Publishing
  • Language: en
  • Pages: 320

A Century of Science Publishing

  • Type: Book
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  • Published: 2001
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  • Publisher: IOS Press

Publishers and observers of the science publishing scene comment in essay form on key developments throughout the 20th century. The scale of the global research effort and its industrial organization have resulted in substantial increases in the published volume, as well as new techniques for its handling.

Scientific Publishing Ecosystem
  • Language: en
  • Pages: 426

Scientific Publishing Ecosystem

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Deep Learning
  • Language: en
  • Pages: 801

Deep Learning

  • Type: Book
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  • Published: 2016-11-10
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  • Publisher: MIT Press

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concep...

Deep Carbon
  • Language: en
  • Pages: 687

Deep Carbon

A comprehensive guide to carbon inside Earth - its quantities, movements, forms, origins, changes over time and impact on planetary processes. This title is also available as Open Access on Cambridge Core.

Deep Learning for the Earth Sciences
  • Language: en
  • Pages: 436

Deep Learning for the Earth Sciences

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares...

How to Publish Academic Books: A Guide to Publishing Monographs, Edited Volumes, Textbooks, and Theses
  • Language: en
  • Pages: 236

How to Publish Academic Books: A Guide to Publishing Monographs, Edited Volumes, Textbooks, and Theses

The academic book publishing sector has a key function when it comes to knowledge production and dissemination across various disciplines. For researchers, scholars, and educators, the process of moving from concept to publication is rarely a trivial task, and often involves the use of imagination, perseverance, and teamwork. Publishing a monograph, an edited volume or a textbook, or turning your thesis into a book can be painful. This book will help you demystify the world of academic book publishing, offering authors a guide to navigating the complicated process with success. This guide aims to provide authors with the knowledge of tools and resources needed to publish a book that reflects...

Deep Time of the Media
  • Language: en
  • Pages: 391

Deep Time of the Media

  • Type: Book
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  • Published: 2008-02-15
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  • Publisher: MIT Press

A quest to find something new by excavating the "deep time" of media's development—not by simply looking at new media's historic forerunners, but by connecting models, machines, technologies, and accidents that have until now remained separated. Deep Time of the Media takes us on an archaeological quest into the hidden layers of media development—dynamic moments of intense activity in media design and construction that have been largely ignored in the historical-media archaeological record. Siegfried Zielinski argues that the history of the media does not proceed predictably from primitive tools to complex machinery; in Deep Time of the Media, he illuminates turning points of media histo...

The Scientific Journal
  • Language: en
  • Pages: 389

The Scientific Journal

Not since the printing press has a media object been as celebrated for its role in the advancement of knowledge as the scientific journal. From open communication to peer review, the scientific journal has long been central both to the identity of academic scientists and to the public legitimacy of scientific knowledge. But that was not always the case. At the dawn of the nineteenth century, academies and societies dominated elite study of the natural world. Journals were a relatively marginal feature of this world, and sometimes even an object of outright suspicion. The Scientific Journal tells the story of how that changed. Alex Csiszar takes readers deep into nineteenth-century London and...

Deep Learning For Physics Research
  • Language: en
  • Pages: 340

Deep Learning For Physics Research

A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.