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Data Structures: Abstraction and Design Using Java, 3rd edition

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Our goal in writing this book was to combine a strong emphasis on problem solving and software design with the study of data structures. To this end, we discuss applications of each data structure to motivate its study. After providing the specification (interface) and the implementation (a Java class), we then cover case studies that use the data structure to solve a significant problem. Examples include maintaining an ordered list, evaluating arithmetic expressions using a stack, finding the shortest path through a maze, and Huffman coding using a binary tree and a priority queue. In the implementation of each data structure and in the solutions of the case studies, we reinforce the message “Think, then code” by performing a thorough analysis of the problem and then carefully designing a solution (using pseudocode and UML class diagrams) before the implementation. We also provide a performance analysis when appropriate. Readers gain an understanding of why different data structures are needed, the applications they are suited for, and the advantages and disadvantages of their possible implementations.

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Linear Mixed-Effects Models Using R: A Step-by-Step Approach
Linear Mixed-Effects Models Using R: A Step-by-Step Approach
Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data include clustered observations, repeated measurements, longitudinal measurements, multivariate observations, etc.

The aim of our book is to help readers in fitting LMMs using R
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Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks
Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner

Key Features

  • Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide
  • Train different types of neural networks using Tensorflow for...
Data Analysis with Open Source Tools
Data Analysis with Open Source Tools

THIS BOOK GREW OUT OFMY EXPERIENCE OF WORKING WITH DATA FOR VARIOUS COMPANIES IN THE TECH industry. It is a collection of those concepts and techniques that I have found to be the most useful, including many topics that I wish I had known earlier—but didn’t.

My degree is in physics, but I also worked as a software...


Introduction to Real Analysis
Introduction to Real Analysis

Assuming minimal background on the part of students, this text gradually develops the principles of basic real analysis and presents the background necessary to understand applications used in such disciplines as statistics, operations research, and engineering. The text presents the first elementary exposition of the gauge integral and...

What is What in the Nanoworld: A Handbook on Nanoscience and Nanotechnology
What is What in the Nanoworld: A Handbook on Nanoscience and Nanotechnology
More than 1,400 entries, from a few sentences to a page in length. The second, completely revised and enlarged edition of this introductory reference handbook summarizes the terms and definitions, most important phenomena, and regulations occurring in the physics, chemistry, technology, and application of nanostructures. A representative collection...
Sketching User Experiences:  Getting the Design Right and the Right Design (Interactive Technologies)
Sketching User Experiences: Getting the Design Right and the Right Design (Interactive Technologies)
There is almost a fervor in the way that new products, with their rich and dynamic interfaces, are being released to the public-typically promising to make lives easier, solve the most difficult of problems, and maybe even make the world a better place. The reality is that few survive, much less deliver on their promise. The folly? An absence of...
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