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  • Safari, an O’Reilly Media Company.  (4)
  • Electronic books  (3)
  • Audiobooks  (1)
  • Computer Science  (4)
  • Law
  • 1
    Online Resource
    Online Resource
    Deep Learning with Python : Learn Best Practices of Deep Learning Models with PyTorch (2021)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484253649
    Language: English
    Pages: 1 online resource (316 pages)
    Edition: 2nd edition
    Parallel Title: Erscheint auch als Ketkar, Nikhil Deep learning with Python
    RVK:
    RB 10104
    RVK:
    ST 302
    Keywords: Electronic books ; local ; Electronic books ; Deep learning ; Python ; PyTorch
    Abstract: Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook’s Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural networks, long short-term memory networks, autoencoders and generative adversarial networks. Backed by a number of tricks of the trade for training and optimizing deep learning models, this edition of Deep Learning with Python explains the best practices in taking these models to production with PyTorch. What You'll Learn Review machine learning fundamentals such as overfitting, underfitting, and regularization. Understand deep learning fundamentals such as feed-forward networks, convolution neural networks, recurrent neural networks, automatic differentiation, and stochastic gradient descent. Apply in-depth linear algebra with PyTorch Explore PyTorch fundamentals and its building blocks Work with tuning and optimizing models Who This Book Is For Beginners with a working knowledge of Python who want to understand Deep Learning in a practical, hands-on manner.
    Note: Online resource; Title from title page (viewed April 9, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    The Art of Writing Efficient Programs (2021)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781800208117
    Language: English
    Pages: 1 online resource (464 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als Pikus, Fedor G. The art of writing efficient programs
    RVK:
    ST 250
    Keywords: Electronic books
    Abstract: Get to grips with various performance improvement techniques such as concurrency, lock-free programming, atomic operations, parallelism, and memory management Key Features Understand the limitations of modern CPUs and their performance impact Find out how you can avoid writing inefficient code and get the best optimizations from the compiler Learn the tradeoffs and costs of writing high-performance programs Book Description The great free lunch of "performance taking care of itself" is over. Until recently, programs got faster by themselves as CPUs were upgraded, but that doesn't happen anymore. The clock frequency of new processors has almost peaked. New architectures provide small improvements to existing programs, but this only helps slightly. Processors do get larger and more powerful, but most of this new power is consumed by the increased number of processing cores and other "extra" computing units. To write efficient software, you now have to know how to program by making good use of the available computing resources, and this book will teach you how to do that. The book covers all the major aspects of writing efficient programs, such as using CPU resources and memory efficiently, avoiding unnecessary computations, measuring performance, and how to put concurrency and multithreading to good use. You'll also learn about compiler optimizations and how to use the programming language (C++) more efficiently. Finally, you'll understand how design decisions impact performance. By the end of this book, you'll not only have enough knowledge of processors and compilers to write efficient programs, but you'll also be able to understand which techniques to use and what to measure while improving performance. At its core, this book is about learning how to learn. What you will learn Discover how to use the hardware computing resources in your programs effectively Understand the relationship between memory order and memory barriers Familiarize yourself with the performance implications of different data structures and organizations Assess the performance impact of concurrent memory accessed and how to minimize it Discover when to use and when not to use lock-free programming techniques Explore different ways to improve the effectiveness of compiler optimizations Design APIs for concurrent data structures and high-performance data structures to avoid inefficiencies Who this book is for This book is for experienced developers and programmers who work ...
    Note: Online resource; Title from title page (viewed October 22, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Ontologies with Python : Programming OWL 2.0 Ontologies with Python and Owlready2 (2020)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484265529
    Language: English
    Pages: 1 online resource (353 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als Jean-Baptiste, Lamy Ontologies with Python
    RVK:
    ST 250
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Use ontologies in Python, with the Owlready2 module developed for ontology-oriented programming. You will start with an introduction and refresher on Python and OWL ontologies. Then, you will dive straight into how to access, create, and modify ontologies in Python. Next, you will move on to an overview of semantic constructs and class properties followed by how to perform automatic reasoning. You will also learn about annotations, multilingual texts, and how to add Python methods to OWL classes and ontologies. Using medical terminologies as well as direct access to RDF triples is also covered. Python is one of the most used programming languages, especially in the biomedical field, and formal ontologies are also widely used. However, there are limited resources for the use of ontologies in Python. Owlready2, downloaded more than 60,000 times, is a response to this problem, and this book is the first one on the topic of using ontologies with Python. What You Will Learn Use Owlready2 to access and modify OWL ontologies in Python Publish ontologies on dynamic websites Perform automatic reasoning in Python Use well-known ontologies, including DBpedia and Gene Ontology, and terminological resources, such as UMLS (Unified Medical Language System) Integrate Python methods in OWL ontologies Who Is This Book For Beginner to experienced readers from biomedical sciences and artificial intelligence fields would find the book useful.
    Note: Online resource; Title from title page (viewed December 17, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    The Filter Bubble (2011)
    [Erscheinungsort nicht ermittelbar] : Tantor Media, Inc. | Boston, MA : Safari
    Details
    ISBN: 9781452621814
    Language: English
    Pages: 1 online resource (27185 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als Pariser, Eli, 1980 - The filter bubble
    Parallel Title: Erscheint auch als Pariser, Eli, 1980 - The filter bubble
    DDC: 004.678
    RVK:
    AP 18420
    RVK:
    SR 850
    RVK:
    MS 7965
    Keywords: Audiobooks ; Internet ; Internet ; Social aspects ; Invisible Web ; Internet ; Censorship ; Web search engines ; Target marketing ; Selective dissemination of information ; Infomediaries ; Influence ; Online information services industry ; Political activity ; Internet ; Informationsfilterung ; Soziologie ; Filter
    Abstract: In December 2009, Google began customizing its search results for each user. Instead of giving you the most broadly popular result, Google now tries to predict what you are most likely to click on. According to MoveOn.org board president Eli Pariser, Google's change in policy is symptomatic of the most significant shift to take place on the Web in recent years-the rise of personalization. In this groundbreaking investigation of the new hidden Web, Pariser uncovers how this growing trend threatens to control how we consume and share information as a society-and reveals what we can do about it. Though the phenomenon has gone largely undetected until now, personalized filters are sweeping the Web, creating individual universes of information for each of us. Facebook-the primary news source for an increasing number of Americans-prioritizes the links it believes will appeal to you so that if you are a liberal, you can expect to see only progressive links. Even an old-media bastion like The Washington Post devotes the top of its home page to a news feed with the links your Facebook friends are sharing. Behind the scenes, a burgeoning industry of data companies is tracking your personal information to sell to advertisers, from your political leanings to the color you painted your living room to the hiking boots you just browsed on Zappos. In a personalized world, we will increasingly be typed and fed only news that is pleasant, familiar, and confirms our beliefs-and because these filters are invisible, we won't know what is being hidden from us. Our past interests will determine what we are exposed to in the future, leaving less room for the unexpected encounters that spark creativity, innovation, and the democratic exchange of ideas. While we all worry that the Internet is eroding privacy or shrinking our attention spans, Pariser uncovers a more pernicious and far-reaching trend and shows how we can-and must-change course. With vivid detail and remarkable scope, The Filter Bubble reveals how personalization undermines the Internet's original purpose as an open platform for the spread of ideas and could leave us all in an isolated, echoing world.
    Note: Online resource; Title from title page (viewed May 12, 2011) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
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