||Angular: Up and Running|
This book will demystify Angular as a framework, as well as provide clear instructions and examples on how to get started with writing scalable Angular applications.
Angular: Up & Running covers most of the major pieces of Angular, but in a structured manner that is generally used in hands-on training. Each chapter takes one concept, and use examples to cover how it works. Problems to work on (with solutions) at the end of each chapter reinforce the learnings of each chapter and allow readers to really get hands-on with Angular. ...
||Continuous Delivery in Java|
With 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; ...
||Learning Apache Drill|
Apache Drill enables interactive analysis of massively large datasets, allowing you to execute SQL queries against data in many different data sources - including Hadoop and MongoDB clusters, HBase, or even your local file system - and get results quickly. With this practical guide, analysts and data scientists focused on business or research applications will learn how to incorporate Drill capabilities into complex programs, including how to use Drill queries to replace some MapReduce operations in a large-scale program.
Drill committers Charles Givre and Paul Rogers provide an introduction to Drill and its ability to handle large files containing data in flexible formats with nested data structures and tables. You'll discover how this capability fills a gap in the Hadoop ecosystem.
Additional topics show you how to:Prepare and organize data to maximize Drill performance;Set expectations for Drill performance on different data types and volumes;Reconcil ...
||Applied Text Analysis with Python|
The programming landscape of natural language processing has changed dramatically in the past few years. Machine learning approaches now require mature tools like Python's scikit-learn to apply models to text at scale. This practical guide shows programmers and data scientists who have an intermediate-level understanding of Python and a basic understanding of machine learning and natural language processing how to become more proficient in these two exciting areas of data science.
This book presents a concise, focused, and applied approach to text analysis with Python, and covers topics including text ingestion and wrangling, basic machine learning on text, classification for text analysis, entity resolution, and text visualization. Applied Text Analysis with Python will enable you to design and develop language-aware data products.
You'll learn how and why machine learning algorithms make decisions about language to analyze text; how to ingest, wrangle, and preprocess language d ...
||Natural Language Processing with PyTorch|
Natural Language Processing (NLP) offers unbounded opportunities for solving interesting problems in artificial intelligence, making it the latest frontier for developing intelligent, deep learning-based applications. If you're a developer or researcher ready to dive deeper into this rapidly growing area of artificial intelligence, this practical book shows you how to use the PyTorch deep learning framework to implement recently discovered NLP techniques. To get started, all you need is a machine learning background and experience programming with Python.
Authors Delip Rao and Goku Mohandas provide you with a solid grounding in PyTorch, and deep learning algorithms, for building applications involving semantic representation of text. Each chapter includes several code examples and illustrations.Get extensive introductions to NLP, deep learning, and PyTorch;Understand traditional NLP methods, including NLTK, SpaCy, and gensim;Explore embeddings: high quality ...
||Stream Processing with Apache Flink|
Get started with Apache Flink, the open source framework that enables you to process streaming data - such as user interactions, sensor data, and machine logs - as it arrives. With this practical guide, you'll learn how to use Apache Flink's stream processing APIs to implement, continuously run, and maintain real-world applications.
Authors Fabian Hueske, one of Flink's creators, and Vasia Kalavri, a core contributor to Flink's graph processing API (Gelly), explains the fundamental concepts of parallel stream processing and shows you how streaming analytics differs from traditional batch data analysis. Software engineers, data engineers, and system administrators will learn the basics of Flink's DataStream API, including the structure and components of a common Flink streaming application.Solve real-world problems with Apache Flink's DataStream API;Set up an environment for developing stream processing applications for Flink;Design streaming applications an ...
Streaming data is a big deal in big data these days, and for good reason. Businesses crave ever more timely data, and streaming is a good way to achieve lower latency. Plus, streaming is a much easier way to tame the massive, unbounded data sets that are increasingly common today.
Expanded from co-author Tyler Akidau's popular series of blog posts "Streaming 101" and "Streaming 102", this practical book shows data engineers, data scientists, and developers how to work with streaming or event-time data in a conceptual and platform-agnostic way. You'll go from "101"-level understanding of stream processing to a nuanced grasp of the what, where, when, and how of processing real-time data streams.
Dive deep into topics including watermarks and windowing, as well as state and timers in the context of stream processing. Although the book uses Apache Beam code snippets to make examples concrete, it presents a general and broad explanation of streaming that's not tied to a specific frame ...
Organizations - big and small - have started to realize just how crucial system and application reliability is to their business. At the same time, they've also learned just how difficult it is to maintain that reliability while iterating at the speed demanded by the marketplace. Site Reliability Engineering (SRE) is a proven approach to this challenge.
SRE is a large and rich topic to discuss. Google led the way with Site Reliability Engineering, the wildly successful O'Reilly book that described Google's creation of the discipline and the implementation that has allowed them to operate at a planetary scale. Inspired by that earlier work, this book explores a very different part of the SRE space.
The more than two dozen chapters in Seeking SRE bring you into some of the important conversations going on in the SRE world right now. Listen as engineers and other leaders in the field discuss different ways of implementing SRE and SRE principles in a wide variety of settings; how SRE ...
||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 ...
||Making Data Visual|
You have a mound of data front of you and a suite of computation tools at your disposal. Which parts of the data actually matter? Where is the insight hiding? If you're a data scientist trying to navigate the murky space between data and insight, this practical book shows you how to make sense of your data through high-level questions, well-defined data analysis tasks, and visualizations to clarify understanding and gain insights along the way.
When incorporated into the process early and often, iterative visualization can help you refine the questions you ask of your data. Authors Danyel Fisher and Miriah Meyer provide detailed case studies that demonstrate how this process can evolve in the real world.
You'll learn:The data counseling process for moving from general to more precise questions about your data, and arriving at a working visualization;The role that visual representations play in data discovery;Common visualization types by the tasks they f ...