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Spring Persistence with Hibernate, 2nd Edition
Spring Persistence with Hibernate, 2nd Edition

Learn how to use the core Hibernate APIs and tools as part of the Spring Framework. This book illustrates how these two frameworks can be best utilized. Other persistence solutions available in Spring are also shown including the Java Persistence API (JPA). Spring Persistence with Hibernate, Second Edition has been updated to cover Spring Framework version 4 and Hibernate version 5. After reading and using this book, you'll have the fundamentals to apply these persistence solutions into your own mission-critical enterprise Java applications that you build using Spring. Persistence is an important set of techniques and technologies for accessing and using data, and ensuring that data is mobile regardless of specific applications and contexts. In Java development, persistence is a key factor in enterprise, e-commerce, and other transaction-oriented applications. Today, the agile and open source Spring Framework is the leading out-of-the-box, open source solution for enterprise Java ...
Pro Angular, 2nd Edition
Pro Angular, 2nd Edition

Get the most from Angular 2, the leading framework for building dynamic JavaScript applications. Best-selling author Adam Freeman begins by describing the MVC pattern and the benefits it can offer and then shows you how to use Angular in your projects, starting from the nuts-and-bolts and building up to the most advanced and sophisticated features, going in-depth to give you the knowledge you need. Each topic is covered clearly and concisely and is packed with the details you need to learn to be truly effective. The most important features are given a no-nonsense in-depth treatment and chapters include common problems and details of how to avoid them. ...
Mastering Machine Learning with Python in Six Steps
Mastering Machine Learning with Python in Six Steps

Master 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 ...
Laravel: Up and Running
Laravel: Up and Running

What sets Laravel apart from other PHP web frameworks? Speed and simplicity, for starters. This rapid application development framework and its vast ecosystem of tools let you quickly build new sites and applications with clean, readable code. With this practical guide, Matt Stauffer - a leading teacher and developer in the Laravel community - provides the definitive introduction to one of today's most popular web frameworks. The book's high-level overview and concrete examples will help experienced PHP web developers get started with Laravel right away. By the time you reach the last page, you should feel comfortable writing an entire application in Laravel from scratch. Dive into several features of this framework, including:Blade, Laravel's powerful, custom templating tool;Tools for gathering, validating, normalizing, and filtering user-provided data;Laravel's Eloquent ORM for working with the application's databases;The Illuminate request ob ...
Foundations for Analytics with Python
Foundations for Analytics with Python

If you're like many of Excel's 750 million users, you want to do more with your data - like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in different formats - by using Python. After author Clinton Brownley takes you through Python basics, you'll be able to write simple scripts for processing data in spreadsheets as well as databases. You'll also learn how to use several Python modules for parsing files, grouping data, and producing statistics. No programming experience is necessary.Create and run your own Python scripts by learning basic syntax;Use Python's csv module to read and parse CSV files;Read multiple Excel worksheets and workbooks with the xlrd module;Perform database operations in MySQL or with the mysqlclient module;Create Python applications to find spe ...
Mastering Azure Analytics
Mastering Azure Analytics

Microsoft 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 ...
Learning Node, 2nd Edition
Learning Node, 2nd Edition

Take your web development skills from browser to server with Node - and learn how to write fast, highly scalable network applications on this JavaScript-based platform. Updated for the latest Node Long Term Support (LTS) and Node Current (6.0) releases, this hands-on edition helps you master Node's core fundamentals and gain experience with several built-in and contributed modules. Get up to speed on Node's event-driven, asynchronous I/O model for developing data-intensive applications that are frequently accessed but computationally simple. If you're comfortable working with JavaScript, this book provides many programming and deployment examples to help you take advantage of server-side development with Node.Explore the frameworks and functionality for full-stack Node development;Dive into Node's module system and package management support;Test your application or module code on the fly with Node's REPL console;Use core Node modules to build web ...
Scalable Cloud Ops with Fugue
Scalable Cloud Ops with Fugue

Cloud computing represents the greatest shift in computing in more than a decade. But the promise of the cloud is unrealized. The cloud isn't just about shedding the physical data center - it's about shedding the data center mindset. Cloud infrastructure can be controlled via API calls. This means we can view it as a giant general-purpose computer - and program it. That's where the Fugue operating system and the Ludwig language come in. They automate the creation, operation, enforcement, and termination of infrastructure in the cloud. This definitive Fugue guide starts with a simple website and moves on to a more robust application with evolving infrastructure needs as you walk through the steps to harnessing the cloud. With Amazon Web Services, launch infrastructure quickly. Debug in design time. Automate deployment and enforcement of your cloud. Centralize your change control process and automate continuous auditing. Rest easy knowing configuration drift, unwanted changes, and inf ...
A Common-Sense Guide to Data Structures and Algorithms
A Common-Sense Guide to Data Structures and Algorithms

Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language; examples in the book are in JavaScript, Python, and Ruby. Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such a ...
Designing Web APIs
Designing Web APIs

Designing an API is complicated to begin with, but evolving your API design over time makes the process even more difficult. There are several books on the topic, but none that guide you through key decisions for designing and building APIs for specific audiences and types of products. Well, until now, that is. Using case studies from companies such as Slack, Stripe, Facebook, and Github, this practical guide shows you how to navigate complex decisions when building, scaling, and evolving your own APIs. You'll learn best practices for designing APIs that developers will love, and discover how to evolve your APIs as your product grows. Developers, architects, tech leads, product managers, and engineering managers will:Examine strategies to expose data through web APIs, using webhooks, websockets, and HTTP;Learn how to evolve APIs while keeping them consistent;Be able to scale APIs with pagination and rate limiting;Handle security, performance, mo ...
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