Complex Network Analysis in PythonComplex network analysis used to be done by hand or with non-programmable network analysis tools, but not anymore! You can now automate and program these tasks in Python. Complex networks are collections of connected items, words, concepts, or people. By exploring their structure and individual elements, we can learn about their meaning, evolution, and resilience.
Starting with simple networks, convert real-life and synthetic network graphs into networkx data structures. Look at more sophisticated networks and learn more powerful machinery to handle centrality calculation, blockmodeling, and clique and community detection. Get familiar with presentation-quality network visualization tools, both programmable and interactive—such as Gephi, a CNA explorer. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute. Each part in the book gives you an overview of a class of networks, includes a practical study ...
Modern Java RecipesThe introduction of functional programming concepts in Java SE 8 was a drastic change for this venerable object-oriented language. Lambda expressions, method references, and streams fundamentally changed the idioms of the language, and many developers have been trying to catch up ever since. This cookbook will help. With more than 70 detailed recipes, author Ken Kousen shows you how to use the newest features of Java to solve a wide range of problems.
For developers comfortable with previous Java versions, this guide covers nearly all of Java SE 8, and includes a chapter focused on changes coming in Java 9. Need to understand how functional idioms will change the way you write code? This cookbook - chock full of use cases - is for you.
Recipes cover: The basics of lambda expressions and method references; Interfaces in the java.util.function package; Stream operations for transforming and filtering data; Comparators and Collectors for sorting and converting streaming data; Combining ...
Practical Machine Learning with PythonMaster the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully.
Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code.
Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. ...
Oracle Business Intelligence with Machine LearningUse machine learning and Oracle Business Intelligence Enterprise Edition (OBIEE) as a comprehensive BI solution. This book follows a when-to, why-to, and how-to approach to explain the key steps involved in utilizing the artificial intelligence components now available for a successful OBIEE implementation. Oracle Business Intelligence with Machine Learning covers various technologies including using Oracle OBIEE, R Enterprise, Spatial Maps, and machine learning for advanced visualization and analytics.
The machine learning material focuses on learning representations of input data suitable for a given prediction problem. This book focuses on the practical aspects of implementing machine learning solutions using the rich Oracle BI ecosystem. The primary objective of this book is to bridge the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to machine learning with OBIEE. ...
Mastering Machine Learning with Python in Six StepsMaster machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner.
This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages.
You'll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining / analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you'll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation.
All the code presented in the book will be available in the form of iPython ...
AnsibleThis book is your concise guide to Ansible, the simple way to automate apps and IT infrastructure. In less than 250 pages, this book takes you from knowing nothing about configuration management to understanding how to use Ansible in a professional setting.
You will learn how to create an Ansible playbook to automatically set up an environment, ready to install an open source project. You'll extract common tasks into roles that you can reuse across all your projects, and build your infrastructure on top of existing open source roles and modules that are available for you to use. You will learn to build your own modules to perform actions specific to your business. By the end you will create an entire cluster of virtualized machines, all of which have your applications and all their dependencies installed automatically. Finally, you'll test your Ansible playbooks.
Ansible can do as much or as little as you want it to. Ansible: From Beginner to Pro will teach you the key skills you ...
Mastering Azure AnalyticsMicrosoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution.
You'll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs.Understand the fundamental patterns of the data lake and lambda architecture;Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them;Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs;Understand where Azure Machine Learning fits i ...
A Swift Kickstart, 2nd EditionThis is the perfect book for the experienced developer who wants to get serious about learning the Swift programming language. If you know at least one modern programming language, this book will teach you how to think and program in Swift. Swift's design is inspired by elements from object-oriented, functional, and generic programming.
As the language matures and improves, this book changes to reflect the latest best practices and coding style. This second edition to the best-selling Swift introduction has been updated to the latest Swift 4 release. It's never been easier to get started with Swift as this edition supports the new iOS Swift Playgrounds along with improved support for Xcode playgrounds. This means you can code along on a Mac or an iPad.
The book begins with an introduction to basic components of programming in Swift: functions, variables and constants, collections, and types from the Swift Standard Library. In the second part, create and use your own enumerations, ...
Continuous Delivery in JavaWith the release of Java 9 and the increasing maturity of web/microservice frameworks such as Spring Boot and Eclipse MicroProfile, there's never been a better time to design and implement Java-powered applications. But Java is only a small piece of the puzzle when it comes to continuously delivering working applications to a production environment.
This practical book charts the journey for establishing the practices and tooling to develop, operate and use a continuous delivery build pipeline for Java applications that will be deployed to a platform such as Kubernetes, AWS Lambda, and other cloud-based services. Each chapter focuses on a key practice within continuous delivery, and outlines appropriate tooling and describes how this should be utilized.Understand the process of continuous delivery, from setting up a local development environment through to deploying into production, and explore how this impacts the skills required from a modern Java application developer; ...
Exploring Java 9Discover all the new features and changes in Java 9, including module systems - JPMS or Project Jigsaw. This book covers the whole Java application development life cycle. You'll review all the important concepts, including module descriptor, unnamed module, automatic module, and command line tools.
Exploring Java 9 also serves as a practical guide for migration to module systems. Code samples from real-world scenarios solidify a foundation for learning and development and allow you to apply best practices in actual development.
Additionally, you'll learn about concurrency, ECMAScript 6 features in Nashorn and Parser API, stack-walking API, Stream and Optional, utilities classes, and I/O. And it's now possible to build modularized applications in Java. You'll see how JPMS affects not only the JDK itself, but also applications that are developed upon it. ...