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Java 9 Modularity: Patterns and Practices for Developing Maintainable Applications

Java 9 Modularity: Patterns and Practices for Developing Maintainable Applications

The upcoming Java 9 module system will affect existing applications and offer new ways of creating modular and maintainable applications. with this hands-on book, Java developers will learn not only about the joys of modularity, but also about the patterns needed to create truly modular and reliable applications. Authors Sander Mak and Paul Bakker teach you the concepts behind the Java 9 module system, along with the new tools it offers. Youíll also gain learn how to modularize existing code and how to build new Java applications in a modular way.

Understand Java 9 module system concepts
Master the patterns and practices for building truly modular applications
Migrate existing applications and libraries to Java 9 modules
Use JDK 9 tools for modular development and migration

Data science for Business

Data science for Business

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You'll not only learn how to improve communication between business stakeholders and data scientists but also how participate intelligently in your company's data science projects. You'll also discover how to think data-analytically and fully appreciate how data science methods can support business decision-making.

  • Understand how data science fits in your organization - and how you can use it for competitive advantage.
  • Treat data as a business asset that requires careful investment if you're to gain real value.
  • Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way.
  • Learn general concepts for actually extracting knowledge from data.
  • Apply data science principles when interviewing data science job candidates.

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, Scikit-Learn and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

With this handbook, you'll learn how to use:
IPython and Jupyter: provide computational environments for data scientists using Python
NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python
Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
Matplotlib: includes capabilities for a flexible range of data visualizations in Python
Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms.

Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

this practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems such as loading data, Handling text or numerical data, model selection, and dimensionality reduction and many other topics.
Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications.
you'll find recipes for:

  • handling numerical and categorical data, text, images, and dates and times

  • Model evaluation and selection
  • saving and loading trained models

  • .

    Linux System Programming: Talking Directly to the Kernel and C Library, Second Edition

    Linux System Programming: Talking Directly to the Kernel and C Library, Second Edition

    All Indian Reprints of O'Reilly are printed in Grayscale.

    Write software that draws directly on services offered by the Linux kernel and core system libraries. With this comprehensive book, Linux kernel contributor Robert Love provides you with a tutorial on Linux system programming, a reference manual on Linux system callsand an insider’s guide to writing smarter, faster code.

    Love clearly distinguishes between POSIX standard functions and special services offered only by Linux. With a new chapter on multithreading, this updated and expanded edition provides an in-depth look at Linux from both a theoretical and applied perspective over a wide range of programming topics, including:

    • A Linux kernel, C libraryand C compiler overview
    • Basic I/O operations, such as reading from and writing to files
    • Advanced I/O interfaces, memory mappingsand optimization techniques
    • The family of system calls for basic process management
    • Advanced process management, including real-time processes
    • Thread concepts, multithreaded programmingand Pthreads
    • File and directory management
    • Interfaces for allocating memory and optimizing memory access
    • Basic and advanced signal interfacesand their role on the system
    • Clock management, including POSIX clocks and high-resolution timers

    Building Evolutionary Architectures: Support Constant Change

    Building Evolutionary Architectures: Support Constant Change

    All Indian Reprints of O'Reilly are printed in Grayscale.

    The software development ecosystem is constantly changing, providing a constant stream of new tools, frameworks, techniquesand paradigms. Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural characteristics as it evolves. This practical guide ties those parts together with a new way to think about architecture and time.

    Domain-Driven Design Distilled

    Domain-Driven Design Distilled

    Domain-Driven Design (DDD) software modeling delivers powerful results in practice, not just in theory, which is why developers worldwide are rapidly moving to adopt it. Now, for the first time, there's an accessible guide to the basics of DDD: What it is, what problems it solves, how it works, and how to quickly gain value from it. Concise, readable, and actionable, Domain-Driven Design Distilled never buries you in detail-it focuses on what you need to know to get results. Vaughn Vernon, author of the best-selling Implementing Domain-Driven Design, draws on his twenty years of experience applying DDD principles to real-world situations. He is uniquely well-qualified to demystify its complexities, illuminate its subtleties, and help you solve the problems you might encounter. Vernon guides you through each core DDD technique for building better software. You'll learn how to segregate domain models using the powerful Bounded Contexts pattern, to develop a Ubiquitous Language within an explicitly bounded context, and to help domain experts and developers work together to create that language. Vernon shows how to use Subdomains to handle legacy systems and to integrate multiple Bounded Contexts to define both team relationships and technical mechanisms. Domain-Driven Design Distilled brings DDD to life. Whether you're a developer, architect, analyst, consultant, or customer, Vernon helps you truly understand it so you can benefit from its remarkable power. Coverage includes What DDD can do for you and your organization-and why it's so important The cornerstones of strategic design with DDD: Bounded Contexts and Ubiquitous Language Strategic design with Subdomains Context Mapping: helping teams work together and integrate software more strategically Tactical design with Aggregates and Domain Events Using project acceleration and management tools to establish and maintain team cadence

    Software Architecture in Practice, 3rd Edition

    Software Architecture in Practice, 3rd Edition

    The award-winning and highly influential Software Architecture in Practice, Third Edition, has been substantially revised to reflect the latest developments in the field. In a real-world setting, the book once again introduces the concepts and best practices of software architecture-how a software system is structured and how that system's elements are meant to interact. Distinct from the details of implementation, algorithm, and data representation, an architecture holds the key to achieving system quality, is a reusable asset that can be applied to subsequent systems, and is crucial to a software organization's business strategy. The authors have structured this edition around the concept of architecture influence cycles. Each cycle shows how architecture influences, and is influenced by, a particular context in which architecture plays a critical role. Contexts include technical environment, the life cycle of a project, an organization's business profile, and the architect's professional practices. The authors also have greatly expanded their treatment of quality attributes, which remain central to their architecture philosophy-with an entire chapter devoted to each attribute-and broadened their treatment of architectural patterns.

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