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National Association of Broadcasters Engineering Handbook
The NAB Engineering Handbook provides detailed information on virtually every aspect of the broadcast chain, from news gathering, program production and postproduction through master control and distribution links to transmission, antennas, RF propagation, cable and satellite. Hot topics covered include HD Radio, HDTV, 2 GHz broadcast auxiliary services, EAS, workflow, metadata, digital asset management, advanced video and audio compression, audio and video over IP, and Internet broadcasting. A wide range of related topics that engineers and managers need to understand are also covered, including broadcast administration, FCC practices, technical standards, security, safety, disaster plannin...
NASA Technical Note
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Foreign Service List
Includes field staffs of Foreign Service, U. S. missions to international organizations, Agency for International Development, ACTION, U.S. Information Agency, Peace Corps, Foreign Agricultural Service, and Department of Army, Navy and Air Force.
NASA Memorandum
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Mechanics for a New Millennium
This volume contains the proceedings of the 2000 International Congress of Theoretical and Applied Mechanics. The book captures a snapshot view of the state of the art in the field of mechanics and will be invaluable to engineers and scientists from a variety of disciplines.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and ...
