Language : English
Published : 2018
Pages : 320
Out of stock
This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
For undergraduate systems analysis and design courses. This Global Edition has been edited to include enhancements making it more relevant to students outside the United States Kendall and Kendall’s Systems Analysis and Design, 9e, is a human-centered book that concisely presents the latest systems development methods, tools, and techniques to students in an engaging and easy-to-understand manner.
Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many new exercises and problems have been added for this edition. As of the third edition, this textbook is published exclusively by the MIT Press. The hardcover edition does not include a dust jacket.
About the Author
Thomas H. Cormen is Professor of Computer Science and former Director of the Institute for Writing and Rhetoric at Dartmouth College. He is the coauthor (with Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein) of the leading textbook on computer algorithms, Introduction to Algorithms (third edition, MIT Press, 2009). Charles E. Leiserson is Professor of Computer Science and Engineering at the Massachusetts Institute of Technology. Ronald L. Rivest is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. Clifford Stein is Professor of Industrial Engineering and Operations Research at Columbia University.
Developed as the text for the basic computer architecture course at MIT, this book integrates a thorough coverage of digital logic design with a comprehensive presentation of computer architecture. It spans the entire range of topics from analog circuit design to operating systems. The authors seek to demystify the construction of computing hardware by illustrating systematically how it is built up from digital circuits through higher-level components to processors and memories, and how its design is affected by its intended uses. “Computation Structures” is unusually broad in scope, considering many real-world problems and trade-off decisions faced by practicing engineers. These difficult choices are confronted and given careful attention throughout the book. Topics addressed include the digital abstraction; digital representations and notation; combinational devices and circuits; sequence and state; synthesis of digital systems; finite state machines; control structures and disciplines; performance measures and trade offs; communication; interpretation; micro-interpreter architecture; microprogramming and microcode; single sequence machines; stack architectures; register architectures; reduced instruction set computers; memory architectures; processes and processor multiplexing; process synchronization; interrupts, priorities, and real time; directions and trends.