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Good Habits for Great Coding: Improving Programming Skills with Examples in Python
Good Habits for Great Coding: Improving Programming Skills with Examples in Python

Improve your coding skills and learn how to write readable code. Rather than teach basic programming, this book presumes that readers understand the fundamentals, and offers time-honed best practices for style, design, documenting, testing, refactoring, and more. 

Taking an informal, conversational tone,...

Introduction to the Design and Analysis of Algorithms (3rd Edition)
Introduction to the Design and Analysis of Algorithms (3rd Edition)
Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal...
Graphs, Networks and Algorithms (Algorithms and Computation in Mathematics)
Graphs, Networks and Algorithms (Algorithms and Computation in Mathematics)

This is the third edition of the classic textbook on the subject. With its clear writing, strong organization, and comprehensive coverage of essential theory it is like a personal guide through this important topic, and now has lots of extra material.

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Combinatorial Optimization: Theory and Algorithms (Algorithms and Combinatorics)
Combinatorial Optimization: Theory and Algorithms (Algorithms and Combinatorics)

This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the...

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

Art of Computer Programming, Volume 2: Seminumerical Algorithms (3rd Edition)
Art of Computer Programming, Volume 2: Seminumerical Algorithms (3rd Edition)

The bible of all fundamental algorithms and the work that taught many of today's software developers most of what they know about computer programming.

 

Byte, September 1995

 

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Sensors: Theory, Algorithms, and Applications (Springer Optimization and Its Applications)
Sensors: Theory, Algorithms, and Applications (Springer Optimization and Its Applications)
In recent years, technological advances have resulted in the rapid development of a new exciting research direction – the interdisciplinary use of sensors for data collection, systems analysis, and monitoring. Application areas include military surveillance, environmental screening, computational neuroscience,...
Computational Optimization, Methods and Algorithms (Studies in Computational Intelligence)
Computational Optimization, Methods and Algorithms (Studies in Computational Intelligence)

Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for...

Data Structures and Algorithms Using Python and C++
Data Structures and Algorithms Using Python and C++
THIS BOOK is intended for use in a traditional college-level data structures course (commonly known as CS2). This book assumes that students have learned the basic syntax of Python and been exposed to the use of existing classes. Most traditional CS1 courses that use Python will have covered all the necessary topics, and some may have covered a...
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Now updated—the systematic introductory guide to modern analysis of large data sets

As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...

Computational Geometry: Algorithms and Applications, Second Edition
Computational Geometry: Algorithms and Applications, Second Edition
This well-accepted introduction to computational geometry is a textbook for high-level undergraduate and low-level graduate courses. The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational...
Python Data Science Handbook: Essential Tools for Working with Data
Python Data Science Handbook: Essential Tools for Working with Data

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib,...

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