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Encyclopedia of Information Science and Technology, Fourth Edition

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In recent years, our world has experienced a profound shift and progression in available computing and knowledge sharing innovations. These emerging advancements have developed at a rapid pace, disseminating into and affecting numerous aspects of contemporary society. This has created a pivotal need for an innovative compendium encompassing the latest trends, concepts, and issues surrounding this relevant discipline area. During the past 15 years, the Encyclopedia of Information Science and Technology has become recognized as one of the landmark sources of the latest knowledge and discoveries in this discipline.

The Encyclopedia of Information Science and Technology, Fourth Edition is a 10-volume set which includes 705 original and previously unpublished research articles covering a full range of perspectives, applications, and techniques contributed by thousands of experts and researchers from around the globe. This authoritative encyclopedia is an all-encompassing, well-established reference source that is ideally designed to disseminate the most forward-thinking and diverse research findings. With critical perspectives on the impact of information science management and new technologies in modern settings, including but not limited to computer science, education, healthcare, government, engineering, business, and natural and physical sciences, it is a pivotal and relevant source of knowledge that will benefit every professional within the field of information science and technology and is an invaluable addition to every academic and corporate library.

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Machine Learning and Security: Protecting Systems with Data and Algorithms
Machine Learning and Security: Protecting Systems with Data and Algorithms

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security...

Algorithms in a Nutshell: A Practical Guide
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Develop, validate, and deploy powerful decentralized applications using blockchain 


Get the most out of cutting-edge blockchain technology using the hands-on information contained in this comprehensive resource. Written by a team of technology and legal experts, Blockchain:...

Cracking Codes with Python: An Introduction to Building and Breaking Ciphers
Cracking Codes with Python: An Introduction to Building and Breaking Ciphers

Learn how to program in Python while making and breaking ciphers—algorithms used to create and send secret messages! 

After a crash course in Python programming basics, you’ll learn to make, test, and hack programs that encrypt text with classical ciphers like the transposition cipher and Vigenère
...

TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

Deep Learning Cookbook: Practical Recipes to Get Started Quickly
Deep Learning Cookbook: Practical Recipes to Get Started Quickly

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve...

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