Computer Systems That Learn
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Author | : Sholom M. Weiss |
Publisher | : Morgan Kaufmann Publishers |
Total Pages | : 248 |
Release | : 1991 |
Genre | : Computers |
ISBN | : |
This text is a practical guide to classification learning systems and their applications, which learn from sample data and make predictions for new cases. The authors examine prominent methods from each area, using an engineering approach and taking the practitioner's point of view.
Author | : Randal E.. Bryant |
Publisher | : |
Total Pages | : 962 |
Release | : 2013-07-23 |
Genre | : Computer programming |
ISBN | : 9781292025841 |
For Computer Systems, Computer Organization and Architecture courses in CS, EE, and ECE departments. Few students studying computer science or computer engineering will ever have the opportunity to build a computer system. On the other hand, most students will be required to use and program computers on a near daily basis. Computer Systems: A Programmer's Perspective introduces the important and enduring concepts that underlie computer systems by showing how these ideas affect the correctness, performance, and utility of application programs. The text's hands-on approach (including a comprehensive set of labs) helps students understand the under-the-hood operation of a modern computer system and prepares them for future courses in systems topics such as compilers, computer architecture, operating systems, and networking.
Author | : J. Stanley Warford |
Publisher | : Jones & Bartlett Learning |
Total Pages | : 731 |
Release | : 2009-06-23 |
Genre | : Computers |
ISBN | : 0763771449 |
Computer Architecture/Software Engineering
Author | : Barry Blundell |
Publisher | : |
Total Pages | : 314 |
Release | : 2007 |
Genre | : Computer networks |
ISBN | : 9781408031292 |
Author | : Harold L Rogler |
Publisher | : |
Total Pages | : |
Release | : 2021-07-13 |
Genre | : |
ISBN | : 9781524929688 |
Author | : Jerome H. Saltzer |
Publisher | : Morgan Kaufmann |
Total Pages | : 561 |
Release | : 2009-05-21 |
Genre | : Computers |
ISBN | : 0080959423 |
Principles of Computer System Design is the first textbook to take a principles-based approach to the computer system design. It identifies, examines, and illustrates fundamental concepts in computer system design that are common across operating systems, networks, database systems, distributed systems, programming languages, software engineering, security, fault tolerance, and architecture.Through carefully analyzed case studies from each of these disciplines, it demonstrates how to apply these concepts to tackle practical system design problems. To support the focus on design, the text identifies and explains abstractions that have proven successful in practice such as remote procedure call, client/service organization, file systems, data integrity, consistency, and authenticated messages. Most computer systems are built using a handful of such abstractions. The text describes how these abstractions are implemented, demonstrates how they are used in different systems, and prepares the reader to apply them in future designs.The book is recommended for junior and senior undergraduate students in Operating Systems, Distributed Systems, Distributed Operating Systems and/or Computer Systems Design courses; and professional computer systems designers. - Concepts of computer system design guided by fundamental principles - Cross-cutting approach that identifies abstractions common to networking, operating systems, transaction systems, distributed systems, architecture, and software engineering - Case studies that make the abstractions real: naming (DNS and the URL); file systems (the UNIX file system); clients and services (NFS); virtualization (virtual machines); scheduling (disk arms); security (TLS) - Numerous pseudocode fragments that provide concrete examples of abstract concepts - Extensive support. The authors and MIT OpenCourseWare provide on-line, free of charge, open educational resources, including additional chapters, course syllabi, board layouts and slides, lecture videos, and an archive of lecture schedules, class assignments, and design projects
Author | : Daniel N. Osherson |
Publisher | : Bradford Books |
Total Pages | : 205 |
Release | : 1990 |
Genre | : Psychology |
ISBN | : 9780262650243 |
Systems That Learn presents a mathematical framework for the study of learning in a variety of domains. It provides the basic concepts and techniques of learning theory as well as a comprehensive account of what is currently known about a variety of learning paradigms.Daniel N. Osherson and Scott Weinstein are at MIT, and Michael Stob at Calvin College.
Author | : Daniel N. Osherson |
Publisher | : |
Total Pages | : 205 |
Release | : 1986 |
Genre | : Learning |
ISBN | : |
Author | : Jasni Mohamad Zain |
Publisher | : Springer |
Total Pages | : 789 |
Release | : 2011-06-28 |
Genre | : Computers |
ISBN | : 364222170X |
This Three-Volume-Set constitutes the refereed proceedings of the Second International Conference on Software Engineering and Computer Systems, ICSECS 2011, held in Kuantan, Malaysia, in June 2011. The 190 revised full papers presented together with invited papers in the three volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on software engineering; network; bioinformatics and e-health; biometrics technologies; Web engineering; neural network; parallel and distributed; e-learning; ontology; image processing; information and data management; engineering; software security; graphics and multimedia; databases; algorithms; signal processing; software design/testing; e- technology; ad hoc networks; social networks; software process modeling; miscellaneous topics in software engineering and computer systems.
Author | : M.G. Sumithra |
Publisher | : Walter de Gruyter GmbH & Co KG |
Total Pages | : 214 |
Release | : 2022-12-31 |
Genre | : Computers |
ISBN | : 3110750589 |
Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.