Best Upcoming Algorithms Books of May 2017

Every month, new books are released, and we’d like to share the ones with you we think should not be missed. This time, we’re focussing on Algorithms. Please let us know what you think, and happy reading!

Best Upcoming Algorithms Books of May 2017

  • Windows Internals, Part 1: System architecture, processes, threads, memory management, and more (7th Edition)
    Windows Internals, Part 1: System architecture, processes, threads, memory management, and more (7th Edition)

    The definitive guide–fully updated for Windows 10 and Windows Server 2016 Delve inside Windows architecture and internals, and see how core components work behind the scenes. Led by a team of internals experts, this classic guide has been fully updated for Windows 10 and Windows Server 2016. This book will help you: · Understand the Window system architecture and its most important entities, such as processes and threads · Examine how processes manage resources and threads scheduled for execution inside processes · Observe how Windows manages virtual and physical memory · Dig into the Windows I/O system and see how device drivers work and integrate with the rest of the system · Go inside the Windows security model to see how it manages access, auditing, and authorization, and learn about the new mechanisms in Windows 10 and Server 2016.

  • Java 9 Programming By Example
    Java 9 Programming By Example

    You will learn the new features of Java 9 quickly and experience a simple and powerful approach to software development. You will be able to use the Java runtime tools, understand the Java environment, and create Java programs. 0, this book will guide you to get employed as a top notch Java developer.

  • Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
    Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis

    Newly added chapters and sections cover topics including normal distributions, sample complexity, VC dimension, Rademacher complexity, power laws and related distributions, cuckoo hashing, and the Lovasz Local Lemma. Material relevant to machine learning and big data analysis enables students to learn modern techniques and applications. Among the many new exercises and examples are programming-related exercises that provide students with excellent training in solving relevant problems.

  • Advanced Analytics with Spark: Patterns for Learning from Data at Scale
    Advanced Analytics with Spark: Patterns for Learning from Data at Scale

    In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. Updated for Spark 2. With this book, you will: Familiarize yourself with the Spark programming model Become comfortable within the Spark ecosystem Learn general approaches in data science Examine complete implementations that analyze large public datasets Discover which machine learning tools make sense for particular problems Acquire code that can be adapted to many uses.

  • Java 9 Data Structures and Algorithms
    Java 9 Data Structures and Algorithms

    Key Features This book provides complete coverage of reactive and functional data structures Based on the latest version of Java 9, this book illustrates the impact of new features on data structures Gain exposure to important concepts such as Big-O Notation and Dynamic Programming Book Description Java 9 Data Structures and Algorithms will cover classical, functional, and reactive data structures, giving you the ability to understand computational complexity, solve problems, and write efficient code. We start off with the basics of algorithms and data structures, helping you understand the fundamentals and measure complexity. What you will learn Understand the fundamentals of algorithms, data structures, and measurement of complexity Find out what general purpose data structures are, including arrays, linked lists, double ended linked lists, and circular lists Get a grasp on the basics of abstract data types-stack, queue, and double ended queue See how to use recursive functions and immutability while understanding and in terms of recursion Handle reactive programming and its related data structures Use binary search, sorting, and efficient sorting-quicksort and merge sort Work with the important concept of trees and list all nodes of the tree, traversal of tree, search trees, and balanced search trees Apply advanced general purpose data structures, priority queue-based sorting, and random access immutable linked lists Gain a better understanding of the concept of graphs, directed and undirected graphs, undirected trees, and much more.

  • Algorithmic Diagnosis of Symptoms and Signs
    Algorithmic Diagnosis of Symptoms and Signs

    ” Effectively evaluate more conditions through new algorithms for various symptoms and laboratory tests, including algorithms representing diseases that are symptoms of other diseases. Recognize diagnostic alternatives at a glance thanks to differential diagnostic tables. Your book purchase includes a complimentary download of the enhanced eBook for iOS, Android, PC & Mac.

  • Practical Machine Learning Cookbook
    Practical Machine Learning Cookbook

    The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations.

  • On Sets and Graphs: Perspectives on Logic and Combinatorics
    On Sets and Graphs: Perspectives on Logic and Combinatorics

    This treatise presents an integrated perspective on the interplay of set theory and graph theory, providing an extensive selection of examples that highlight how methods from one theory can be used to better solve problems originated in the other. Features: explores the interrelationships between sets and graphs and their applications to finite combinatorics; introduces the fundamental graph-theoretical notions from the standpoint of both set theory and dyadic logic, and presents a discussion on set universes; explains how sets can conveniently model graphs, discussing set graphs and set-theoretic representations of claw-free graphs; investigates when it is convenient to represent sets by graphs, covering counting and encoding problems, the random generation of sets, and the analysis of infinite sets; presents excerpts of formal proofs concerning graphs, whose correctness was verified by means of an automated proof-assistant; contains numerous exercises, examples, definitions, problems and insight panels.

  • Once Upon an Algorithm: How Stories Explain Computing (MIT Press)
    Once Upon an Algorithm: How Stories Explain Computing (MIT Press)

    In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem solving. This simple daily routine solves a recurring problem through a series of well-defined steps.

  • Innovations in Computer Science and Engineering: Proceedings of the Fourth ICICSE 2016 (Lecture Notes in Networks and Systems)
    Innovations in Computer Science and Engineering: Proceedings of the Fourth ICICSE 2016 (Lecture Notes in Networks and Systems)

    The book is a collection of high-quality peer-reviewed research papers presented at the Fourth International Conference on Innovations in Computer Science and Engineering (ICICSE 2016) held at Guru Nanak Institutions, Hyderabad, India during 22 – 23 July 2016. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field ofdata science and analytics, artificial intelligence and expert systems, mobility, cloud computing, network security, and emerging technologies.

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