UNESCO Science Report

UNESCO Science Report PDF Author: UNESCO
Publisher: UNESCO Publishing
ISBN: 9231004506
Category : Political Science
Languages : en
Pages : 757

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UNESCO Science Report

UNESCO Science Report PDF Author: UNESCO
Publisher: UNESCO Publishing
ISBN: 9231004506
Category : Political Science
Languages : en
Pages : 757

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Book Description


Master and Chief Mate

Master and Chief Mate PDF Author: International Maritime Organization
Publisher: IMO Publishing
ISBN: 9280161032
Category : Merchant marine
Languages : en
Pages : 344

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Cryptography and Network Security

Cryptography and Network Security PDF Author: William Stallings
Publisher: Pearson
ISBN: 0134484525
Category : Computers
Languages : en
Pages : 772

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Book Description
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. The Principles and Practice of Cryptography and Network Security Stallings’ Cryptography and Network Security, Seventh Edition, introduces the reader to the compelling and evolving field of cryptography and network security. In an age of viruses and hackers, electronic eavesdropping, and electronic fraud on a global scale, security is paramount. The purpose of this book is to provide a practical survey of both the principles and practice of cryptography and network security. In the first part of the book, the basic issues to be addressed by a network security capability are explored by providing a tutorial and survey of cryptography and network security technology. The latter part of the book deals with the practice of network security: practical applications that have been implemented and are in use to provide network security. The Seventh Edition streamlines subject matter with new and updated material — including Sage, one of the most important features of the book. Sage is an open-source, multiplatform, freeware package that implements a very powerful, flexible, and easily learned mathematics and computer algebra system. It provides hands-on experience with cryptographic algorithms and supporting homework assignments. With Sage, the reader learns a powerful tool that can be used for virtually any mathematical application. The book also provides an unparalleled degree of support for the reader to ensure a successful learning experience.

Cryptography and Network Security

Cryptography and Network Security PDF Author:
Publisher: Krishna Prakashan Media
ISBN: 9788182830271
Category :
Languages : en
Pages : 388

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Cryptography and Network Security

Cryptography and Network Security PDF Author: William Stallings
Publisher: Prentice Hall
ISBN: 0136097049
Category : Computers
Languages : en
Pages : 899

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Book Description
This text provides a practical survey of both the principles and practice of cryptography and network security.

Deep Learning on Windows

Deep Learning on Windows PDF Author: Thimira Amaratunga
Publisher: Apress
ISBN: 9781484264300
Category : Computers
Languages : en
Pages : 235

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Book Description
Build deep learning and computer vision systems using Python, TensorFlow, Keras, OpenCV, and more, right within the familiar environment of Microsoft Windows. The book starts with an introduction to tools for deep learning and computer vision tasks followed by instructions to install, configure, and troubleshoot them. Here, you will learn how Python can help you build deep learning models on Windows. Moving forward, you will build a deep learning model and understand the internal workings of a convolutional neural network on Windows. Further, you will go through different ways to visualize the internal workings of deep learning models along with an understanding of transfer learning where you will learn how to build a model architecture and use data augmentations. Next, you will manage and train deep learning models on Windows before deploying your application as a web application. You’ll also do some basic image processing and work with computer vision options that will help you build various applications with deep learning. Finally, you will use generative adversarial networks along with reinforcement learning. After reading Deep Learning on Windows, you will be able to design deep learning models and web applications on the Windows operating system. What You Will Learn Get deep learning tools working on Microsoft Windows Understand model visualization techniques, such as the built-in plot_model function of Keras and third-party visualization tools Build a robust training script Convert your deep learning model into a web application Generate handwritten digits with DCGAN (deep convolutional generative adversarial network) Understand the basics of reinforcement learning Who This Book Is For AI developers and enthusiasts wanting to work on the Windows platform.

Computer Security

Computer Security PDF Author: William Stallings
Publisher: Pearson Higher Ed
ISBN: 0133072630
Category : Computers
Languages : en
Pages : 817

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Book Description
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Computer Security: Principles and Practice, 2e, is ideal for courses in Computer/Network Security. In recent years, the need for education in computer security and related topics has grown dramatically – and is essential for anyone studying Computer Science or Computer Engineering. This is the only text available to provide integrated, comprehensive, up-to-date coverage of the broad range of topics in this subject. In addition to an extensive pedagogical program, the book provides unparalleled support for both research and modeling projects, giving students a broader perspective. The Text and Academic Authors Association named Computer Security: Principles and Practice, 1e, the winner of the Textbook Excellence Award for the best Computer Science textbook of 2008.

Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT PDF Author: Amita Kapoor
Publisher: Packt Publishing Ltd
ISBN: 1788832760
Category : Computers
Languages : en
Pages : 382

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Book Description
Build smarter systems by combining artificial intelligence and the Internet of Things—two of the most talked about topics today Key FeaturesLeverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT dataProcess IoT data and predict outcomes in real time to build smart IoT modelsCover practical case studies on industrial IoT, smart cities, and home automationBook Description There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models. By the end of this book, you will be able to build smart AI-powered IoT apps with confidence. What you will learnApply different AI techniques including machine learning and deep learning using TensorFlow and KerasAccess and process data from various distributed sourcesPerform supervised and unsupervised machine learning for IoT dataImplement distributed processing of IoT data over Apache Spark using the MLLib and H2O.ai platformsForecast time-series data using deep learning methodsImplementing AI from case studies in Personal IoT, Industrial IoT, and Smart CitiesGain unique insights from data obtained from wearable devices and smart devicesWho this book is for If you are a data science professional or a machine learning developer looking to build smart systems for IoT, Hands-On Artificial Intelligence for IoT is for you. If you want to learn how popular artificial intelligence (AI) techniques can be used in the Internet of Things domain, this book will also be of benefit. A basic understanding of machine learning concepts will be required to get the best out of this book.

Charter of Ethics of Science and Technology in the Arab Region

Charter of Ethics of Science and Technology in the Arab Region PDF Author: UNESCO Office Cairo and Regional Bureau for Science in the Arab States
Publisher: UNESCO Publishing
ISBN: 9231003585
Category :
Languages : en
Pages : 30

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Programming PyTorch for Deep Learning

Programming PyTorch for Deep Learning PDF Author: Ian Pointer
Publisher: O'Reilly Media
ISBN: 1492045322
Category : Computers
Languages : en
Pages : 220

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Book Description
Take the next steps toward mastering deep learning, the machine learning method that’s transforming the world around us by the second. In this practical book, you’ll get up to speed on key ideas using Facebook’s open source PyTorch framework and gain the latest skills you need to create your very own neural networks. Ian Pointer shows you how to set up PyTorch on a cloud-based environment, then walks you through the creation of neural architectures that facilitate operations on images, sound, text,and more through deep dives into each element. He also covers the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production. Learn how to deploy deep learning models to production Explore PyTorch use cases from several leading companies Learn how to apply transfer learning to images Apply cutting-edge NLP techniques using a model trained on Wikipedia Use PyTorch’s torchaudio library to classify audio data with a convolutional-based model Debug PyTorch models using TensorBoard and flame graphs Deploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud