JavaScript Design Patterns. Deliver fast and efficient production-grade JavaScript applications at scale

Hugo Di Francesco

Unlock the potential of JavaScript design patterns, the foundation for development teams seeking structured and reusable solutions to common software development challenges in this guide to improving code maintainability, scalability, and performance. Discover how these patterns equip businesses with cleaner and more maintainable code, promote team collaboration, reduce errors, and save time and costs.This book provides a comprehensive view of design patterns in modern (ES6+) JavaScript with real-world examples of their deployment in professional settings. You’ll start by learning how to use creational, structural, and behavioral design patterns in idiomatic JavaScript, and then shift focus to the architecture and UI patterns. Here, you’ll learn how to apply patterns for libraries such as React and extend them further to general web frontend and micro frontend approaches. The last section of the book introduces and illustrates sets of performance and security patterns, including messaging and events, asset and JavaScript loading strategies, and asynchronous programming performance patterns.Throughout the book, examples featuring React and Next.js, in addition to JavaScript and Web API examples, will help you choose and implement proven design patterns across diverse web ecosystems, transforming the way you approach development.

Practical Data Analysis. For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that

Hector Cuesta

Plenty of small businesses face big amounts of data but lack the internal skills to support quantitative analysis. Understanding how to harness the power of data analysis using the latest open source technology can lead them to providing better customer service, the visualization of customer needs, or even the ability to obtain fresh insights about the performance of previous products. Practical Data Analysis is a book ideal for home and small business users who want to slice and dice the data they have on hand with minimum hassle.Practical Data Analysis is a hands-on guide to understanding the nature of your data and turn it into insight. It will introduce you to the use of machine learning techniques, social networks analytics, and econometrics to help your clients get insights about the pool of data they have at hand. Performing data preparation and processing over several kinds of data such as text, images, graphs, documents, and time series will also be covered.Practical Data Analysis presents a detailed exploration of the current work in data analysis through self-contained projects. First you will explore the basics of data preparation and transformation through OpenRefine. Then you will get started with exploratory data analysis using the D3js visualization framework. You will also be introduced to some of the machine learning techniques such as, classification, regression, and clusterization through practical projects such as spam classification, predicting gold prices, and finding clusters in your Facebook friends' network. You will learn how to solve problems in text classification, simulation, time series forecast, social media, and MapReduce through detailed projects. Finally you will work with large amounts of Twitter data using MapReduce to perform a sentiment analysis implemented in Python and MongoDB. Practical Data Analysis contains a combination of carefully selected algorithms and data scrubbing that enables you to turn your data into insight.

Computer Architecture with Python and ARM. Learn how computers work, program your own, and explore assembly language on Raspberry Pi

Alan Clements

This comprehensive guide offers a unique and immersive learning experience by combining Python programming with ARM architecture.Starting with an introduction to computer architecture and the flow of data within a computer system, you’ll progress to building your own interpreter using Python. You’ll see how this foundation enables the simulation of computer operations and learn ways to enhance a simulator by adding new instructions and displaying improved results.As you advance, you’ll explore the TC1 Assembler and Simulator Program to gain insights into instruction analysis and explore practical examples of simulators. This will help you build essential skills in understanding complex computer instructions, strengthening your grasp of computer architecture. Moreover, you’ll be introduced to the Raspberry Pi operating system, preparing you to delve into the detailed language of the ARM computer. This includes exploring the ARM instruction set architecture, data-processing instructions, subroutines, and the stack.With clear explanations, practical examples, and coding exercises, this resource will enable you to design and construct your own computer simulator, simulate assembly language programs, and leverage the Raspberry Pi for ARM programming.

Cloudera Administration Handbook. A complete, hands-on guide to building and maintaining large Apache Hadoop clusters using Cloudera Manager and CDH5

Rohit Menon

Getting Started with Meteor.js JavaScript Framework. Learn to develop powerful web applications in minutes with Meteor

Isaac Strack

Expert Python Programming. Become a master in Python by learning coding best practices and advanced programming concepts in Python 3.7 - Third Edition

Michał Jaworski, Tarek Ziadé

Python is a dynamic programming language that's used in a wide range of domains thanks to its simple yet powerful nature. Although writing Python code is easy, making it readable, reusable, and easy to maintain is challenging. Complete with best practices, useful tools, and standards implemented by professional Python developers, the third edition of Expert Python Programming will help you overcome this challenge.The book will start by taking you through the new features in Python 3.7. You'll then learn the advanced components of Python syntax, in addition to understanding how to apply concepts of various programming paradigms, including object-oriented programming, functional programming, and event-driven programming. This book will also guide you through learning the naming best practices, writing your own distributable Python packages, and getting up to speed with automated ways to deploy your software on remote servers. You’ll discover how to create useful Python extensions with C, C++, Cython, and CFFI. Furthermore, studying about code management tools, writing clear documentation, and exploring test-driven development will help you write clean code.By the end of the book, you will have become an expert in writing efficient and maintainable Python code.

Big Data Analytics with R. Leverage R Programming to uncover hidden patterns in your Big Data

Simon Walkowiak

Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing.The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.

RESTful Java Web Services Security. Secure your RESTful applications against common vulnerabilities with this book and

René Enríquez