This practically-focused textbook presents a concise tutorial on data structures and algorithms using the object-functional language Scala. The material builds upon the foundation established in the title Programming ...
ISBN:
(数字)9783030125615
ISBN:
(纸本)9783030125608
This practically-focused textbook presents a concise tutorial on data structures and algorithms using the object-functional language Scala. The material builds upon the foundation established in the title Programming with Scala: Language Exploration by the same author, which can be treated as a companion text for those less familiar with Scala. topics and features: discusses data structures and algorithms in the form of design patterns; covers key topics on arrays, lists, stacks, queues, hash tables, binary trees, sorting, searching, and graphs; describes examples of complete and running applications for each topic; presents a functional approach to implementations for data structures and algorithms (excepting arrays); provides numerous challenge exercises (with solutions), encouraging the reader to take existing solutions and improve upon them; offers insights from the author's extensive industrial experience; includes a glossary, and an appendix supplying an overview of discrete mathematics. Highlighting the techniques and skills necessary to quickly derive solutions to applied problems, this accessible text will prove invaluable to time-pressured students and professional software engineers.
topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs’ run-times, and by engineering analysis of obtained results fo...
详细信息
ISBN:
(数字)9783319988337
ISBN:
(纸本)9783319988320
topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs’ run-times, and by engineering analysis of obtained results for improved parallel execution performances.
This invaluable textbook presents a comprehensive introduction to modern competitive programming. The text highlights how competitive programming has proven to be an excellent way to learn algorithms, by encouraging t...
ISBN:
(纸本)9783319725475;3319725475
This invaluable textbook presents a comprehensive introduction to modern competitive programming. The text highlights how competitive programming has proven to be an excellent way to learn algorithms, by encouraging the design of algorithms that actually work, stimulating the improvement of programming and debugging skills, and reinforcing the type of thinking required to solve problems in a competitive setting. The book contains many folklore algorithm design tricks that are known by experienced competitive programmers, yet which have previously only been formally discussed in online forums and blog posts. topics and features: reviews the features of the C++ programming language, and describes how to create efficient algorithms that can quickly process large data sets; discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library; introduces the algorithm design technique of dynamic programming, and investigates elementary graph algorithms; covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries; surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming; examines advanced graph techniques, geometric algorithms, and string techniques; describes a selection of more advanced topics, including square root algorithms and dynamic programming optimization. This easy-to-follow guide is an ideal reference for all students wishing to learn algorithms, and practice for programming contests. Knowledge of the basics of programming is assumed, but previous background in algorithm design or programming contests is not necessary. Due to the broad range of topics covered at various levels of difficulty, this book is suitable for both beginners and more experienced readers.
This easy-to- follow textbook/reference guides the reader through the creation of a fully functional embedded operating system, from its source code, in order to develop a deeper understanding of each component and ho...
ISBN:
(数字)9783319729770
ISBN:
(纸本)9783319729763
This easy-to- follow textbook/reference guides the reader through the creation of a fully functional embedded operating system, from its source code, in order to develop a deeper understanding of each component and how they work together. The text describes in detail the procedure for building the bootloader, kernel, filesystem, shared libraries, start-up scripts, configuration files and system utilities, to produce a GNU/Linux operating system. This fully updated second edition also includes new material on virtual machine technologies such as VirtualBox, Vagrant and the Linux container system Docker. topics and features: presents an overview of the GNU/Linux system, introducing the components of the system, and covering aspects of process management, input/output and environment; discusses containers and the underlying kernel technology upon which they are based; provides a detailed examination of the GNU/Linux filesystem; explains how to build an embedded system under a virtual machine, and how to build an embedded system to run natively on an actual processor;introduces the concept of the compiler toolchain, and reviews the platforms BeagleBone and Raspberry Pi; describes how to build firmware images for devices running the Openwrt operating system. The hands-on nature and clearly structured approach of this textbook will appeal strongly to practically minded undergraduate and graduate level students, as well as to industry professionals involved in this area.
This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most pop...
ISBN:
(数字)9783319730042
ISBN:
(纸本)9783319730035
This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website. topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-forward neural network; describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning; presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism. This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computerscience, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology.
This book offers an engaging introduction to traditional topics in discrete mathematics, in a manner designed to appeal to computerscience students. Presents detailed walkthroughs of several algorithms, along with ex...
ISBN:
(数字)9783319701516
ISBN:
(纸本)9783319701509
This book offers an engaging introduction to traditional topics in discrete mathematics, in a manner designed to appeal to computerscience students. Presents detailed walkthroughs of several algorithms, along with exercises and practical examples throughout.
This book explains the principal techniques of data mining, for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed examples, with a focus on algorithms ...
ISBN:
(数字)9781447173076
ISBN:
(纸本)9781447173069
This book explains the principal techniques of data mining, for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed examples, with a focus on algorithms rather than mathematical formalism.
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