Mastering Spark for Data Science. Lightning fast and scalable data science solutions

Andrew Morgan, Antoine Amend, Matthew Hallett, David George

Data science seeks to transform the world using data, and this is typically achievedthrough disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs.This book deep dives into using Spark to deliver production-grade data sciencesolutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more.You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly.

TensorFlow Machine Learning Cookbook. Over 60 practical recipes to help you master Google’s TensorFlow machine learning library

Nick McClure

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow.This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.

JavaScript by Example. Learn modern web development with real-world applications

Dani Akash S

JavaScript is the programming language that all web developers need to learn. The first item on our JavaScript to-do list is building g a To-do list app, which you'll have done by the end of the first chapter. You'll explore DOM manipulation with JavaScript and work with event listeners. You'll work with images and text to build a Meme creator. You will also learn about ES (ECMAScript) classes, and will be introduced to layouts using the CSS3 Flexbox. You'll also develop a responsive Event Registration form that allows users to register for your upcoming event and use charts and graphics to display registration data. You will then build a weather application, which will show you different ways perform AJAX requests and work with dynamic, external data. WebRTC enables real-time communication in a web browser; you'll learn how to use it when you build a real-time video-call and chat application later in the book. Towards the end of the book, you will meet React, Facebook's JavaScript library for building user interfaces. You'll throw together a blog with React, and get a feel for why this kind of JavaScript framework is used to build large-scale applications. To make your blog more maintainable and scalable, you'll use Redux to manage data across React components.

Real-World SRE. The Survival Guide for Responding to a System Outage and Maximizing Uptime

Nat Welch

Real-World SRE is the go-to survival guide for the software developer in the middle of catastrophic website failure. Site Reliability Engineering (SRE) has emerged on the frontline as businesses strive to maximize uptime. This book is a step-by-step framework to follow when your website is down and the countdown is on to fix it. Nat Welch has battle-hardened experience in reliability engineering at some of the biggest outage-sensitive companies on the internet. Arm yourself with his tried-and-tested methods for monitoring modern web services, setting up alerts, and evaluating your incident response.Real-World SRE goes beyond just reacting to disaster—uncover the tools and strategies needed to safely test and release software, plan for long-term growth, and foresee future bottlenecks. Real-World SRE gives you the capability to set up your own robust plan of action to see you through a company-wide website crisis.The final chapter of Real-World SRE is dedicated to acing SRE interviews, either in getting a first job or a valued promotion.

Machine Learning with Spark. Develop intelligent, distributed machine learning systems - Second Edition

Rajdeep Dua, Manpreet Singh Ghotra

This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML.Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML.By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business.

Google Cloud Platform Cookbook. Implement, deploy, maintain, and migrate applications on Google Cloud Platform

Legorie Rajan PS

Google Cloud Platform is a cloud computing platform that offers products and services to host applications using state-of-the art infrastructure and technology. You can build and host applications and websites, store data, and analyze data on Google's scalable infrastructure. This book follows a recipe-based approach, giving you hands-on experience to make the most of Google Cloud services.This book starts with practical recipes that explain how to utilize Google Cloud's common services. Then, you'll see how to make full use of Google Cloud components such as networking, security, management, and developer tools. Next, we'll deep dive into implementing core Google Cloud services into your organization, with practical recipes on App Engine, Compute Engine, Cloud Functions, virtual networks, and Cloud Storage. Later, we'll provide recipes on implementing authentication and security, Cloud APIs, command-line management, deployment management, and the Cloud SDK. Finally, we'll cover administration and troubleshooting tasks on applications with Compute services and we'll show how to monitor your organization's efficiency with best practices.By the end of this book, you'll have an overall understanding and hands-on implementation of Google Cloud services in your organization with ease.

AWS Automation Cookbook. Continuous Integration and Continuous Deployment using AWS services

Nikit Swaraj

AWS CodeDeploy, AWS CodeBuild, and CodePipeline are scalable services offered by AWS that automate an application's build and deployment pipeline. In order to deliver tremendous speed and agility, every organization is moving toward automating their entire application pipeline. This book will cover all the AWS services required to automate your deployment to your instances.You'll begin by setting up and using one of the AWS services for automation –CodeCommit. Next, you'll learn how to build a sample Maven and NodeJS application using CodeBuild. After you've built the application, you'll see how to use CodeDeploy to deploy the application in EC2/Auto Scaling. You'll also build a highly scalable and fault tolerant Continuous Integration (CI)/Continuous Deployment (CD) pipeline using some easy-to-follow recipes.Following this, you'll achieve CI/CD for a microservice application and reduce the risk within your software development life cycle globally. You'll also learn to set up an infrastructure using CloudFormation templates and Ansible, and see how to automate AWS resources using AWS Lambda.Finally, you'll learn to automate instances in AWS and automate the deployment lifecycle of applications. By the end of this book, you'll be able to minimize application downtime and implement CI/CD, gaining total control over your software development lifecycle.

Python Penetration Testing Cookbook. Practical recipes on implementing information gathering, network security, intrusion detection, and post-exploitation

Rejah Rehim

Penetration testing is the use of tools and code to attack a system in order to assess its vulnerabilities to external threats. Python allows pen testers to create their own tools. Since Python is a highly valued pen-testing language, there are many native libraries and Python bindings available specifically for pen-testing tasks.Python Penetration Testing Cookbook begins by teaching you how to extract information from web pages. You will learn how to build an intrusion detection system using network sniffing techniques. Next, you will find out how to scan your networks to ensure performance and quality, and how to carry out wireless pen testing on your network to avoid cyber attacks. After that, we’ll discuss the different kinds of network attack. Next, you’ll get to grips with designing your own torrent detection program. We’ll take you through common vulnerability scenarios and then cover buffer overflow exploitation so you can detect insecure coding. Finally, you’ll master PE code injection methods to safeguard your network.