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Advanced deep learning with TensorFlow 2 and Keras : apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more
A second edition of the bestselling guide to exploring and mastering deep learning with Keras, updated to include TensorFlow 2.x with new chapters on object detection, semantic segmentation, and unsupervised learning using mutual information.
eBook
NTP security : a quick-start guide
\"Learn the risks associated with Network Time Protocol (NTP) security and how to minimize those risks in daily deployment. Disruption of NTP services can interrupt communication between servers on the network and take an entire network offline. Beyond disrupting communication, flaws in the NTP daemon itself can make servers vulnerable to external attack--attacks that often go unnoticed. NTP is being used more frequently in Distributed Denial of Service (DDoS) attacks. It is a User Datagram Protocol (UDP) with encryption schemes that are not often used or are poorly implemented, making it susceptible to spoofing. Despite all of the security challenges, the fact is that NTP is critical to most modern networks. It is one of those \"set it and forget it\" protocols that network administrators and even security professionals don't understand in depth. However, an attacker who does understand the security flaws can wreak havoc on an insecure network. NTP Security: A Quick-Start Guide provides a deeper understanding of the protocol itself and how to deploy a strategy using the protocol throughout a network in a secure manner. Your security team will be able to provide better guidance to the system and network teams who will then be able to better manage the day-to-day implementation. This succinct resource offers practical guidance to an underserved topic (actually, not served at all). Coverage includes: an understanding of NTP and the importance of time synchronization in modern networks; issues in NTP security, including an analysis of NTP traffic; a review of the vulnerabilities and flaws in the protocol; practical solutions for securing NTP and building a robust infrastructure; effective alternatives to NTP\"--Back cover.
Book
The Structure and Dynamics of Networks
From the Internet to networks of friendship, disease transmission, and even terrorism, the concept--and the reality--of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields--including mathematics, physics, computer science, sociology, and biology--have been pursuing these questions and building a new \"science of networks.\" This book brings together for the first time a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field.
The book is organized into four sections, each preceded by an editors' introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science--the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science.
eBook
Survey of Deep Learning Paradigms for Speech Processing
Over the past decades, a particular focus is given to research on machine learning techniques for speech processing applications. However, in the past few years, research has focused on using deep learning for speech processing applications. This new machine learning field has become a very attractive area of study and has remarkably better performance than the others in the various speech processing applications. This paper presents a brief survey of application deep learning for various speech processing applications such as speech separation, speech enhancement, speech recognition, speaker recognition, emotion recognition, language recognition, music recognition, speech data retrieval, etc. The survey goes on to cover the use of Auto-Encoder, Generative Adversarial Network, Restricted Boltzmann Machine, Deep Belief Network, Deep Neural Network, Convolutional Neural Network, Recurrent Neural Network and Deep Reinforcement Learning for speech processing. Additionally, it focuses on the various speech database and evaluation metrics used by deep learning algorithms for performance evaluation.
Journal Article
The Wealth of Networks
With the radical changes in information production that the Internet has introduced, we stand at an important moment of transition, says Yochai Benkler in this thought-provoking book. The phenomenon he describes as social production is reshaping markets, while at the same time offering new opportunities to enhance individual freedom, cultural diversity, political discourse, and justice. But these results are by no means inevitable: a systematic campaign to protect the entrenched industrial information economy of the last century threatens the promise of today's emerging networked information environment.
In this comprehensive social theory of the Internet and the networked information economy, Benkler describes how patterns of information, knowledge, and cultural production are changing-and shows that the way information and knowledge are made available can either limit or enlarge the ways people can create and express themselves. He describes the range of legal and policy choices that confront us and maintains that there is much to be gained-or lost-by the decisions we make today.
eBook