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Explorations in Computing
An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to
Explorations in Computing
Based on the author’s introductory course at the University of Oregon, Explorations in Computing: An Introduction to Computer Science focuses on the fundamental idea of computation and offers insight into how computation is used to solve a variety of interesting and important real-world problems. Taking an active learning approach, the text encourages students to explore computing ideas by running programs and testing them on different inputs. It also features illustrations by Phil Foglio, winner of the 2009 and 2010 Hugo Award for Best Graphic Novel. Classroom-Tested Material The first four chapters introduce key concepts, such as algorithms and scalability, and hone practical lab skills ...
A Functional Start to Computing with Python
A Functional Start to Computing with Python enables students to quickly learn computing without having to use loops, variables, and object abstractions at the start. Requiring no prior programming experience, the book draws on Python’s flexible data types and operations as well as its capacity for defining new functions. Along with the specifics of Python, the text covers important concepts of computing, including software engineering motivation, algorithms behind syntax rules, advanced functional programming ideas, and, briefly, finite state machines. Taking a student-friendly, interactive approach to teach computing, the book addresses more difficult concepts and abstractions later in th...
A Concise Introduction to Programming in Python
Suitable for newcomers to computer science, A Concise Introduction to Programming in Python provides a succinct, yet complete, first course in computer science using the Python programming language. The book features: Short, modular chapters with brief and precise explanations, intended for one class period Early introduction of basic procedural constructs such as functions, selection, and repetition, allowing them to be used throughout the course Objects are introduced in the middle of the course, and class design comes toward the end Examples, exercises, and projects from a wide range of application domains, including biology, physics, images, sound, mathematics, games, and textual analysis No external libraries are required, simplifying the book’s use in common lab spaces Each chapter introduces a main idea through a concrete example and a series of exercises. Designed to teach programming in a concise, yet comprehensive way, this book provides a timely introduction for students and anyone interested in learning Python.
Cybersecurity
Cybersecurity: A Practical Engineering Approach introduces the implementation of a secure cyber architecture, beginning with the identification of security risks. It then builds solutions to mitigate risks by considering the technological justification of the solutions as well as their efficiency. The process follows an engineering process model. Each module builds on a subset of the risks, discussing the knowledge necessary to approach a solution, followed by the security control architecture design and the implementation. The modular approach allows students to focus on more manageable problems, making the learning process simpler and more attractive.
Genome Evolution
Table of contents
Advances in Neural Information Processing Systems 16
Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.
Parallel Programming and Compilers
The second half of the 1970s was marked with impressive advances in array/vector architectures and vectorization techniques and compilers. This progress continued with a particular focus on vector machines until the middle of the 1980s. The major ity of supercomputers during this period were register-to-register (Cray 1) or memory-to-memory (CDC Cyber 205) vector (pipelined) machines. However, the increasing demand for higher computational rates lead naturally to parallel comput ers and software. Through the replication of autonomous processors in a coordinated system, one can skip over performance barriers due technology limitations. In princi ple, parallelism offers unlimited performance p...
A Concise Introduction to Data Structures using Java
A student-friendly text, A Concise Introduction to Data Structures Using Java takes a developmental approach, starting with simpler concepts first and then building toward greater complexity. Important topics, such as linked lists, are introduced gradually and revisited with increasing depth. More code and guidance are provided at the beginning, allowing students time to adapt to Java while also beginning to learn data structures. As students develop fluency in Java, less code is provided and more algorithms are outlined in pseudocode. The text is designed to support a second course in computer science with an emphasis on elementary data structures. The clear, concise explanations encourage ...
