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Author : Kyle Loudon
Publisher : "O'Reilly Media, Inc."
Page : 560 pages
File Size : 44,9 Mb
Release : 1999
Category : Computers
ISBN : 9781565924536
A comprehensive guide to understanding the language of C offers solutions for everyday programming tasks and provides all the necessary information to understand and use common programming techniques. Original. (Intermediate).
Author : Kyle Loudon
Publisher : "O'Reilly Media, Inc."
Page : 564 pages
File Size : 46,9 Mb
Release : 1999-08-05
Category : Computers
ISBN : 9780596551957
There are many books on data structures and algorithms, including some with useful libraries of C functions. Mastering Algorithms with C offers you a unique combination of theoretical background and working code. With robust solutions for everyday programming tasks, this book avoids the abstract style of most classic data structures and algorithms texts, but still provides all of the information you need to understand the purpose and use of common programming techniques. Implementations, as well as interesting, real-world examples of each data structure and algorithm, are included. Using both a programming style and a writing style that are exceptionally clean, Kyle Loudon shows you how to use such essential data structures as lists, stacks, queues, sets, trees, heaps, priority queues, and graphs. He explains how to use algorithms for sorting, searching, numerical analysis, data compression, data encryption, common graph problems, and computational geometry. And he describes the relative efficiency of all implementations. The compression and encryption chapters not only give you working code for reasonably efficient solutions, they offer explanations of concepts in an approachable manner for people who never have had the time or expertise to study them in depth. Anyone with a basic understanding of the C language can use this book. In order to provide maintainable and extendible code, an extra level of abstraction (such as pointers to functions) is used in examples where appropriate. Understanding that these techniques may be unfamiliar to some programmers, Loudon explains them clearly in the introductory chapters. Contents include: Pointers Recursion Analysis of algorithms Data structures (lists, stacks, queues, sets, hash tables, trees, heaps, priority queues, graphs) Sorting and searching Numerical methods Data compression Data encryption Graph algorithms Geometric algorithms
Author : Kyle Loudon
Publisher : Unknown
Page : 572 pages
File Size : 53,8 Mb
Release : 1999-01-01
Category : Algorithms
ISBN : 8173661162
There are many books on data structures and algorithms, and some books laying out useful libraries of C functions, but this book aims to give you a unique combination of theoretical background and working code. In offering robust solutions for everyday programming tasks,
Author : Jarkko Hietaniemi,John Macdonald,Jon Orwant
Publisher : "O'Reilly Media, Inc."
Page : 734 pages
File Size : 50,5 Mb
Release : 1999-08-18
Category : Computers
ISBN : 9781449307271
Many programmers would love to use Perl for projects that involve heavy lifting, but miss the many traditional algorithms that textbooks teach for other languages. Computer scientists have identified many techniques that a wide range of programs need, such as: Fuzzy pattern matching for text (identify misspellings!)Finding correlations in dataGame-playing algorithmsPredicting phenomena such as Web trafficPolynomial and spline fitting Using algorithms explained in this book, you too can carry out traditional programming tasks.
Author : Magnus Lie Hetland
Publisher : Apress
Page : 303 pages
File Size : 45,8 Mb
Release : 2014-09-17
Category : Computers
ISBN : 9781484200551
Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others.
Author : Giuseppe Bonaccorso
Publisher : Packt Publishing Ltd
Page : 567 pages
File Size : 51,5 Mb
Release : 2018-05-25
Category : Computers
ISBN : 9781788625906
Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is for This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.
Author : Magnus Lie Hetland
Publisher : Apress
Page : 325 pages
File Size : 43,7 Mb
Release : 2011-02-27
Category : Computers
ISBN : 9781430232384
Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself.
Author : Arthur O'Dwyer
Publisher : Packt Publishing Ltd
Page : 379 pages
File Size : 53,9 Mb
Release : 2017-09-28
Category : Computers
ISBN : 9781787288232
This book breaks down the C++ STL, teaching you how to extract its gems and apply them to your programming. About This Book Boost your productivity as a C++ developer with the latest features of C++17 Develop high-quality, fast, and portable applications with the varied features of the STL Migrate from older versions (C++11, C++14) to C++17 Who This Book Is For This book is for developers who would like to master the C++ STL and make full use of its components. Prior C++ knowledge is assumed. What You Will Learn Make your own iterator types, allocators, and thread pools. Master every standard container and every standard algorithm. Improve your code by replacing new/delete with smart pointers. Understand the difference between monomorphic algorithms, polymorphic algorithms, and generic algorithms. Learn the meaning and applications of vocabulary type, product type and sum type. In Detail Modern C++ has come a long way since 2011. The latest update, C++17, has just been ratified and several implementations are on the way. This book is your guide to the C++ standard library, including the very latest C++17 features. The book starts by exploring the C++ Standard Template Library in depth. You will learn the key differences between classical polymorphism and generic programming, the foundation of the STL. You will also learn how to use the various algorithms and containers in the STL to suit your programming needs. The next module delves into the tools of modern C++. Here you will learn about algebraic types such as std::optional, vocabulary types such as std::function, smart pointers, and synchronization primitives such as std::atomic and std::mutex. In the final module, you will learn about C++'s support for regular expressions and file I/O. By the end of the book you will be proficient in using the C++17 standard library to implement real programs, and you'll have gained a solid understanding of the library's own internals. Style and approach This book takes a concise but comprehensive approach to explaining and applying the C++ STL, one feature at a time.
Author : Robert Sedgewick
Publisher : Unknown
Page : 0 pages
File Size : 52,6 Mb
Release : 1998
Category : C++ (Computer program language)
ISBN : 0201350882
Author : Daniel Zingaro
Publisher : No Starch Press
Page : 409 pages
File Size : 42,5 Mb
Release : 2020-12-15
Category : Computers
ISBN : 9781718500815
A hands-on, problem-based introduction to building algorithms and data structures to solve problems with a computer. Algorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems. Line-by-line breakdowns of the code will teach you how to use algorithms and data structures like: The breadth-first search algorithm to find the optimal way to play a board game or find the best way to translate a book Dijkstra's algorithm to determine how many mice can exit a maze or the number of fastest routes between two locations The union-find data structure to answer questions about connections in a social network or determine who are friends or enemies The heap data structure to determine the amount of money given away in a promotion The hash-table data structure to determine whether snowflakes are unique or identify compound words in a dictionary NOTE: Each problem in this book is available on a programming-judge website. You'll find the site's URL and problem ID in the description. What's better than a free correctness check?
Author : Pedro Domingos
Publisher : Basic Books
Page : 354 pages
File Size : 47,5 Mb
Release : 2015-09-22
Category : Computers
ISBN : 9780465061921
Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.
Author : Gavin Hackeling
Publisher : Packt Publishing Ltd
Page : 254 pages
File Size : 43,9 Mb
Release : 2017-07-24
Category : Computers
ISBN : 9781788298490
Use scikit-learn to apply machine learning to real-world problems About This Book Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks Learn how to build and evaluate performance of efficient models using scikit-learn Practical guide to master your basics and learn from real life applications of machine learning Who This Book Is For This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn Review fundamental concepts such as bias and variance Extract features from categorical variables, text, and images Predict the values of continuous variables using linear regression and K Nearest Neighbors Classify documents and images using logistic regression and support vector machines Create ensembles of estimators using bagging and boosting techniques Discover hidden structures in data using K-Means clustering Evaluate the performance of machine learning systems in common tasks In Detail Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn's API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model's performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach. Style and approach This book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.
Author : Richard M Reese
Publisher : "O'Reilly Media, Inc."
Page : 226 pages
File Size : 46,8 Mb
Release : 2013-05-01
Category : Computers
ISBN : 9781449344559
Improve your programming through a solid understanding of C pointers and memory management. With this practical book, you’ll learn how pointers provide the mechanism to dynamically manipulate memory, enhance support for data structures, and enable access to hardware. Author Richard Reese shows you how to use pointers with arrays, strings, structures, and functions, using memory models throughout the book. Difficult to master, pointers provide C with much flexibility and power—yet few resources are dedicated to this data type. This comprehensive book has the information you need, whether you’re a beginner or an experienced C or C++ programmer or developer. Get an introduction to pointers, including the declaration of different pointer types Learn about dynamic memory allocation, de-allocation, and alternative memory management techniques Use techniques for passing or returning data to and from functions Understand the fundamental aspects of arrays as they relate to pointers Explore the basics of strings and how pointers are used to support them Examine why pointers can be the source of security problems, such as buffer overflow Learn several pointer techniques, such as the use of opaque pointers, bounded pointers and, the restrict keyword
Author : Steve Oualline
Publisher : "O'Reilly Media, Inc."
Page : 576 pages
File Size : 41,8 Mb
Release : 2002-12-13
Category : Computers
ISBN : 9781449367169
C++ is a powerful, highly flexible, and adaptable programming language that allows software engineers to organize and process information quickly and effectively. But this high-level language is relatively difficult to master, even if you already know the C programming language.The 2nd edition of Practical C++ Programming is a complete introduction to the C++ language for programmers who are learning C++. Reflecting the latest changes to the C++ standard, this 2nd edition takes a useful down-to-earth approach, placing a strong emphasis on how to design clean, elegant code.In short, to-the-point chapters, all aspects of programming are covered including style, software engineering, programming design, object-oriented design, and debugging. It also covers common mistakes and how to find (and avoid) them. End of chapter exercises help you ensure you've mastered the material.Practical C++ Programming thoroughly covers: C++ Syntax Coding standards and style Creation and use of object classes Templates Debugging and optimization Use of the C++ preprocessor File input/output Steve Oualline's clear, easy-going writing style and hands-on approach to learning make Practical C++ Programming a nearly painless way to master this complex but powerful programming language.
Author : Ben Klemens
Publisher : "O'Reilly Media, Inc."
Page : 297 pages
File Size : 50,7 Mb
Release : 2012-10-15
Category : Computers
ISBN : 9781449344665
Throw out your old ideas about C and get to know a programming language that’s substantially outgrown its origins. With this revised edition of 21st Century C, you’ll discover up-to-date techniques missing from other C tutorials, whether you’re new to the language or just getting reacquainted. C isn’t just the foundation of modern programming languages; it is a modern language, ideal for writing efficient, state-of-the-art applications. Get past idioms that made sense on mainframes and learn the tools you need to work with this evolved and aggressively simple language. No matter what programming language you currently favor, you’ll quickly see that 21st century C rocks. Set up a C programming environment with shell facilities, makefiles, text editors, debuggers, and memory checkers Use Autotools, C’s de facto cross-platform package manager Learn about the problematic C concepts too useful to discard Solve C’s string-building problems with C-standard functions Use modern syntactic features for functions that take structured inputs Build high-level, object-based libraries and programs Perform advanced math, talk to internet servers, and run databases with existing C libraries This edition also includes new material on concurrent threads, virtual tables, C99 numeric types, and other features.