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Deep Learning for Intrusion Detection

Techniques and Applications

General Audio Signal Processing with Deep Learning

A free ebook version of this title is available through Luminos, University of California Press's Open Access publishing program. Visit www.luminosoa.org to learn more. What if we could start over and build the internet from scratch? How could it be rebuilt or reimagined as more equitable and just? For more than eight years, Britt S. Paris investigated alternative internet infrastructure projects, conducting interviews, site visits, and policy analysis. In this expansive and interdisciplinary study, Paris critically examines the myriad and contradictory promises, utility, and obstacles to building a completely new internet.&nbsp;Radical Infrastructure locates and analyzes the boundaries of how people and groups imagine, build, deploy, maintain, and use the internet as they survive-and even dare to thrive in-challenging political, economic, and environmental contexts. Ultimately, Paris encourages active reflection among scholars, policymakers, and activists and reveals more grounded imaginaries, tactics, and opportunities for future people-centered projects.

Imagining the Internet from the Ground Up

Radical Infrastructure

Learn to secure, build, implement, and test future blockchain applications Blockchain was originally introduced in the crypto-currency of Bitcoin in order to keep track of transactions over a peer-to-peer network to prevent the double-spending of bitcoin. This distributed ledger technology, however, has developed a reputation as a disruptive technology for the transfer of values and disintermediation. Despite this reputation, blockchain is, simply, at its core, a data structure-in this case, a cryptographic hash chain of blocks of transactions-continually replicated and maintained in a distributed manner by a peer-to-peer network of hosts. Together they decide through a specific consensus protocol, what transactions can be registered or added to the blockchain. Blockchain Application Security introduces the reader to the architecture and components of blockchain, as well as blockchain and bitcoin protocol, aimed at a basic level of understanding of the technical perspective. The book discusses the benefits, the vulnerabilities, and even the design flaws found in blockchain applications. It also teaches how to manage the risks of blockchain by deciding how digital assets, data confidentiality, and data availability should be protected from unauthorized access. Blockchain Application Security readers will also find: <ul> <li>An exploration of source code and core APIs relevant to blockchain</li> <li>A glossary of common terminology used for blockchain</li> <li>Real cases of blockchain applications to illustrate points</li></ul>Blockchain Application Security is an ideal resource for application architects, software developers, security auditors, and vulnerability testers of enterprise-based blockchain applications.

How to Design Secure and Attack Resilient Blockchain Applications

Blockchain Application Security

Progress In Data Science

Ubiquitous Laplacian: An Introduction To Numerical Pdes With Applications In Data Science

Building a Program for Strategy and Oversight

Practical AI Governance

Series On Intelligence Science

This popular science compendium provides an approximate, holistic but first ever solution to the four Holy Grail questions: How does a brain work? How does the brain learn? How does its consciousness arise? How does learning require consciousness?The volume explains how human brains require and learn consciousness and why the new AI will overcome the current lack of conscious learning algorithms in AI. For human societies, it suggests how governments can make their taxpayers safer, more prosper and happier. For future AI, it calls for a thorough investigation in scientific infrastructures like government and private funding agencies, publication venues, professional societies and administrators that evaluate research. Why did a conscious learning algorithm not have a healthy environment to study? Why could rampant misconducts of data deletion in deep learning be allowed to grossly exaggerate AI performances for so long? The author's real-life accounts reveal deep reasons.The useful reference text benefits laymen in all walks of life, as well as professionals, researchers, academics and students in any areas.

Conscious Learning: Humans And Machines

A Practical Guide Using Python

Classical Machine Learning

Methods, Applications, and Implications

Adaptive AI in Sensor Informatics

Cybersecurity Implications in Blockchain Architecture

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

A Gentle Introduction to Quantum Machine Learning

Deep Learning for Intrusion Detection

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