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Best Upcoming Algorithms Books of September 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 September 2017

  • Machine Learning with TensorFlow

    The answer is TensorFlow, a new open source Machine Learning library from Google. Machine Learning with TensorFlow teaches readers about machine learning algorithms and how to implement solutions with TensorFlow. Each chapter zooms into a prominent example of machine learning.

  • Bored and Brilliant: How Spacing Out Can Unlock Your Most Productive and Creative Self

    “Bored and Brilliant shows the fascinating side of boredom. ” – Gretchen Rubin, author of the New York Times best seller The Happiness Project It’s time to move “doing nothing” to the top of your to-do list. In this fascinating new audiobook, Manoush explains the connection between boredom and original thinking, exploring how we can harness boredom’s hidden benefits to become our most productive and creative selves, without totally abandoning our gadgets in the process.

  • Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics)

    This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. Finally, it covers numerical linear algebra, beginning with a discussion of the basics of numerical computations, and following up with accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors.

  • Learning C++ Functional Programming

    This book will help you discover all the C++ 17 features that can be applied to build software in a functional way. The second module explains how to efficiently implement C++ features such as pure functions and immutable states to build robust applications. Here, you will also learn to optimize code using metaprogramming in a functional way.

  • Python Machine Learning Case Studies: Five Case Studies for the Data Scientist

    Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. What You Will Learn Gain insights into machine learning concepts Work on real-world applications of machine learning Learn concepts of model selection and optimization Get a hands-on overview of Python from a machine learning point of view Who This Book Is For Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.

  • Handbook of Graph Theory, Second Edition (Discrete Mathematics and Its Applications)

    Reflecting these advances, Handbook of Graph Theory, Second Edition provides comprehensive coverage of the main topics in pure and applied graph theory. This edition also contains notes regarding terminology and notation. With 34 new contributors, this handbook is the most comprehensive single-source guide to graph theory.

  • Reactive Machine Learning Systems

    Machine learning applications autonomously reason about data at massive scale. But machine learning systems are different than other applications when it comes to testing, building, deploying, and monitoring. Reactive Machine Learning Systems teaches readers how to implement reactive design solutions in their machine learning systems to make them as reliable as a well-built web app.

  • Euclidean Distance Geometry: An Introduction (Springer Undergraduate Texts in Mathematics and Technology)

    This textbook, the first of its kind, presents the fundamentals of distance geometry: theory, useful methodologies for obtaining solutions, and real world applications. Descriptive graphics, examples, and problems, accompany the real gems of the text, namely the applications in visualization of graphs, localization of sensor networks, protein conformation from distance data, clock synchronization protocols, robotics, and control of unmanned underwater vehicles, to name several. Aimed at intermediate undergraduates, beginning graduate students, researchers, and practitioners, the reader with a basic knowledge of linear algebra will gain an understanding of the basic theories of distance geometry and why they work in real life.

  • Java 9 Cookbook

    A definitive guide to learning the key concepts of modern application development in Java About This Book Learn the latest features of Java 9 Extend your Java knowledge and take your application to new levels by making it fast, secure, and scalable Delve into the intricacies of Modular programming in Java 9 Who This Book Is For The book is for intermediate to advanced Java programmers who want to make their applications fast, secure, and scalable. What You Will Learn Set up JDK and know the differences in the JDK 9 installation Implement OO designs using classes and interfaces Manage operating system processes Understand the new modular JDK and modular programming Create a modular application with clear dependencies Build graphical user interfaces using JavaFX Use the new HTTP Client API Learn about the new diagnostic features in Java 9 See how to use the new jShell REPL tool Execute ES6-compliant JavaScript code from your Java applications In Detail Java is an object-oriented programming language. Starting with the installation of Java, each recipe addresses a specific problem, with.

  • Handbook of Discrete and Combinatorial Mathematics, Second Edition (Discrete Mathematics and Its Applications)

    Providing a ready reference for practitioners in the field, the Handbook of Discrete and Combinatorial Mathematics, Second Edition presents additional material on Google’s matrix, random graphs, geometric graphs, computational topology, and other key topics. New chapters highlight essential background information on bioinformatics and computational geometry. Each chapter includes a glossary, definitions, facts, examples, algorithms, major applications, and references.

The post Best Upcoming Algorithms Books of September 2017 appeared first on Best Programming Books.



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Best Upcoming Algorithms Books of September 2017

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