Products related to Systems:
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Engineering Deep Learning Systems
Design systems optimized for deep learning models. Written for software engineers, this book teaches you how to implement a maintainable platform for developing deep learning models. In Engineering Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systemsRecognize and solve common engineering challenges for deep learning systemsUnderstand the deep learning development cycleAutomate training for models in TensorFlow and PyTorchOptimize dataset management, training, model serving and hyperparameter tuningPick the right open-source project for your platformEngineering Deep Learning Systems is a practical guide for software engineers and data scientists who are designing and building platforms for deep learning.It's full of hands-on examples that will help you transfer your software development skills to implementing deep learning platforms.You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning.This book is the perfect way to step into an exciting-and lucrative-career as a deep learning engineer. about the technology Behind every deep learning researcher is a team of engineers bringing their models to production.To build these systems, you need to understand how a deep learning system's platform differs from other distributed systems.By mastering the core ideas in this book, you'll be able to support deep learning systems in a way that's fast, repeatable, and reliable.
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Knowledge Integration Methods for Probabilistic Knowledge-based Systems
Knowledge-based systems and solving knowledge integrating problems have seen a great surge of research activity in recent years.Knowledge Integration Methods provides a wide snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency, and methods for integrating knowledge bases.The book also provides the mathematical background to solving problems of restoring consistency and integrating probabilistic knowledge bases in the integrating process.The research results presented in the book can be applied in decision support systems, semantic web systems, multimedia information retrieval systems, medical imaging systems, cooperative information systems, and more.This text will be useful for computer science graduates and PhD students, in addition to researchers and readers working on knowledge management and ontology interpretation.
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Secure Systems Development with UML
Attacks against computer systems can cause considerable economic or physical damage.High-quality development of security-critical systems is difficult, mainly because of the conflict between development costs and verifiable correctness. Jürjens presents the UML extension UMLsec for secure systems development.It uses the standard UML extension mechanisms, and can be employed to evaluate UML specifications for vulnerabilities using a formal semantics of a simplified fragment of UML.Established rules of security engineering can be encapsulated and hence made available even to developers who are not specialists in security.As one example, Jürjens uncovers a flaw in the Common Electronic Purse Specification, and proposes and verifies a correction. With a clear separation between the general description of his approach and its mathematical foundations, the book is ideally suited both for researchers and graduate students in UML or formal methods and security, and for advanced professionals writing critical applications.
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Arthur Erickson on Learning Systems
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Which study is suitable for the development of rocket propulsion systems?
Aerospace engineering or mechanical engineering would be suitable studies for the development of rocket propulsion systems. These fields provide the necessary knowledge of fluid dynamics, thermodynamics, and materials science required to design and optimize rocket engines. Additionally, courses in propulsion systems and aerospace propulsion would be beneficial for gaining specific expertise in this area. Overall, a strong foundation in engineering principles and a focus on propulsion systems would be essential for a career in rocket propulsion development.
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Are stereo systems or 5.1 systems better?
It ultimately depends on the individual's preferences and needs. Stereo systems are great for simple, two-channel audio playback and can provide high-quality sound for music and movies. On the other hand, 5.1 systems offer a more immersive experience with surround sound, making them ideal for home theater setups and gaming. If you prioritize a more immersive and spatial audio experience, a 5.1 system may be better for you. However, if you value simplicity and high-quality audio, a stereo system may be the better choice.
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Why are photovoltaic systems called photovoltaic systems?
Photovoltaic systems are called photovoltaic systems because they directly convert light (photo) into electricity (voltaic). The term "photo" comes from the Greek word for light, and "voltaic" is derived from the name of the Italian physicist Alessandro Volta, who is known for his work in electricity. Therefore, the term "photovoltaic" accurately describes the process by which these systems generate electricity from sunlight.
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How can one prepare for the training as a specialist in application development for IT systems?
To prepare for training as a specialist in application development for IT systems, one can start by gaining a strong foundation in computer science, programming languages, and software development. This can be achieved through formal education such as a degree in computer science or related field, or through self-study and online courses. It's also important to gain practical experience by working on personal projects or internships to apply the theoretical knowledge. Additionally, staying updated with the latest technologies and trends in application development is crucial to be well-prepared for the training.
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Control Systems and Reinforcement Learning
A high school student can create deep Q-learning code to control her robot, without any understanding of the meaning of 'deep' or 'Q', or why the code sometimes fails.This book is designed to explain the science behind reinforcement learning and optimal control in a way that is accessible to students with a background in calculus and matrix algebra.A unique focus is algorithm design to obtain the fastest possible speed of convergence for learning algorithms, along with insight into why reinforcement learning sometimes fails.Advanced stochastic process theory is avoided at the start by substituting random exploration with more intuitive deterministic probing for learning.Once these ideas are understood, it is not difficult to master techniques rooted in stochastic control.These topics are covered in the second part of the book, starting with Markov chain theory and ending with a fresh look at actor-critic methods for reinforcement learning.
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Deep Learning for Vision Systems
Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more.Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life.With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you'll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
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Programming Rust : Fast, Safe Systems Development
Systems programming provides the foundation for the world's computation.Writing performance-sensitive code requires a programming language that puts programmers in control of how memory, processor time, and other system resources are used.The Rust systems programming language combines that control with a modern type system that catches broad classes of common mistakes, from memory management errors to data races between threads. With this practical guide, experienced systems programmers will learn how to successfully bridge the gap between performance and safety using Rust.Jim Blandy, Jason Orendorff, and Leonora Tindall demonstrate how Rust's features put programmers in control over memory consumption and processor use by combining predictable performance with memory safety and trustworthy concurrency. You'll learn:Rust's fundamental data types and the core concepts of ownership and borrowingHow to write flexible, efficient code with traits and genericsHow to write fast, multithreaded code without data racesRust's key power tools: closures, iterators, and asynchronous programmingCollections, strings and text, input and output, macros, unsafe code, and foreign function interfacesThis revised, updated edition covers the Rust 2021 Edition.
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Gene Delivery Systems : Development and Applications
This unique volume in our Drugs and Pharmaceutical Sciences series covers the development of gene therapy today, the technology involved, clinical applications of siRNA, non-viral vector-based mRNA delivery using nanotechnology, and RNA based vaccines for treating the infectious diseases.It also presents the current application of the CRISPR/Cas9 gene-editing technique which has revolutionized genome editing and which was awarded the 2020 Nobel Prize in Chemistry.Several new drug delivery systems are explored for the applications of gene therapy.These are found to be useful in treating chronic illnesses, including cancer and infectious diseases.Key Features: Overview of the development of gene therapy Provides the most up to date information on the development of gene therapy, from the technology involved to gene correction and genome editing Presents CRISPR gene therapy recent trends and applications Discusses siRNA, mRNA, and DNA plasmids
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What is the prior knowledge required for an IT systems merchant?
Prior knowledge required for an IT systems merchant includes a strong understanding of information technology, including hardware, software, networking, and security. Additionally, knowledge of different operating systems, programming languages, and database management is essential. Familiarity with industry standards and best practices, as well as the ability to assess and understand the specific needs of clients, is also important. Finally, a good grasp of market trends, competitive landscape, and customer behavior in the IT industry is crucial for success as an IT systems merchant.
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Is Arabic script the ultimate development of writing systems in the world?
It is subjective to claim that Arabic script is the ultimate development of writing systems in the world as different writing systems have evolved and served their respective languages and cultures effectively. Arabic script is certainly a sophisticated and elegant writing system with a rich history and widespread usage, but it may not be considered the ultimate development as there are other writing systems like Chinese, Latin, and Devanagari that have also played significant roles in the development of human civilization. Each writing system has its unique characteristics and strengths, making it difficult to determine a single ultimate development in the world of writing systems.
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Why are Android systems supported less than Apple iOS systems?
Android systems are supported less than Apple iOS systems for a few reasons. First, the Android ecosystem is more fragmented, with a wide variety of devices and versions of the operating system in use, making it more challenging for developers to create and maintain consistent support. Additionally, Apple has a more controlled and centralized approach to its hardware and software, allowing for more seamless updates and support. Finally, Apple has a reputation for prioritizing user experience and security, which may lead to more consistent and timely support for iOS systems compared to Android.
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What is the difference between solar systems and photovoltaic systems?
Solar systems refer to the entire system of collecting, storing, and distributing solar energy, including solar panels, inverters, batteries, and other components. Photovoltaic systems, on the other hand, specifically refer to the technology that converts sunlight into electricity using solar panels. In other words, photovoltaic systems are a subset of solar systems, focusing solely on the conversion of solar energy into electricity.
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