This book is a practical, handson guide that takes you through the techniques of web scraping using Beautiful Soup. Getting Started with Beautiful Soup is great for anybody who is interested in website scraping and extracting information. However, a basic knowledge of Python, HTML tags, and CSS is required for better understanding.

"Customer Success with Microsft Dynamics Sure Step" is a focused tutorial of Microsoft Dynamics solution envisioning and delivery, rather than a stepbystep guide into project management. It will equip you with the tactics required to plan, align, and orchestrate your solution selling activities, as well as help you to be efficient, proactive, goal driven, and flexible in your Microsoft Dynamics engagements. If you are involved in one or more of the roles stated below, then this book is for you: ?If you are a Project Manager, Engagement Manager, Solution Architect, or Consultant involved in delivering Microsoft Dynamics solutions, this book will teach you how you can improve the quality of your implementation with a consistent, repeatable process. ?If you are a Customer Project Manager, Subject Matter Expert, Key User, or End User involved in selecting the right business solution for your organization and delivering the Microsoft Dynamics solution, this book will help you determine how the method facilitates the delivery of a solution that is aligned to your vision. ?If you are a Sales Executive, Services Sales Executive, Technical Sales Specialist, PreSales Consultant, or Engagement Manager involved in the sales of Microsoft Dynamics solutions, this book will help you to understand how you can accelerate your sales cycle and bring it to a close. ?If you are the Customer Decision Maker, CxO, Buyer, or Project Manager who participates in the selection process for your business solution needs, this book will show you how to determine how this process can help your due diligence exercise and set the stage for a quality implementation of the solution. ?If you are a Change Management expert, this book will enable you to learn how you can help the customer manage organizational change during the business solution delivery process, and/or help solution providers adopt a process for selling and delivering solutions.

If you are a Python programmer or a security researcher who has basic knowledge of Python programming and want to learn about penetration testing with the help of Python, this book is ideal for you. Even if you are new to the field of ethical hacking, this book can help you find the vulnerabilities in your system so that you are ready to tackle any kind of attack or intrusion.

This book is a best fit for backend developers with a basic knowledge of Drupal's APIs and some experience using the command line. Perhaps you already worked on one or two Drupal projects, but have never dived deep into Drush's toolset. In any case, this book will give you a lot of advice by covering real-world challenges in Drupal projects that can be solved using Drush.

If you are a hobbyist who wants to develop projects based on Arduino as the main microcontroller platform or an engineer interested in finding out what the Arduino platform offers, then this book is ideal for you. Some prior knowledge of the C programming language is required.

This book is aimed at those familiar with the basics of Blender, looking to delve into the depths of the Cycles rendering engine to create an array of breath-taking materials and textures.

This book is aimed at developers and technical testers who are looking for a quick way to take their SoapUI skills and understanding to the next level. Even if you are new to SoapUI but have basic Java skills and a reasonable grasp of RESTFul and Soap web services, then you should have no problem making use of this book.

If you have already undertaken some simple projects with the Raspberry Pi and are looking to enter the exciting work of hardware interaction, then this book is ideal for you.

If you are a developer who wants to migrate from Selenium RC or any other automation tool to Selenium WebDriver, then this book is for you. Knowledge of automation tools is necessary to follow the examples in this book.

If you are a security professional whose workload is increasing, or a Puppet professional looking to increase your knowledge of security, or even an experienced systems administrator, then this book is for you. This book will take you to the next level of security automation using Puppet. The book requires no prior knowledge of Puppet to get started.

This book is for anyone who wants to learn Intel Galileo for home automation and cross-platform software development. No knowledge of programming with Intel Galileo is assumed, but knowledge of the C programming language is essential.

If you are an Android developer looking to test your applications or optimize your application development process, then this book is for you. No previous experience in application testing is required.

This book is ideal for developers who have experience in developing websites or possess minor knowledge of how responsive websites work. No experience of high-level website development or performance tweaking is required.

If you are a developer who is experienced with Cocos2d and Objective-C, and want to take your game development skills to the next level, this book is going to help you achieve your goal.

This book is targeted at system engineers and system administrators who want to upgrade their knowledge and skills in high availability and want to learn practically how to achieve high availability with CentOS Linux. You are expected to have good CentOS Linux knowledge and basic networking experience.

This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.

Use PhoneGap to build cross-platform mobile applications quickly and efficiently About This Book Build native mobile phone applications with HTML5, JavaScript, and CSS Incorporate smartphone capabilities such as GPS, camera, accelerometer, and more into your apps for any mobile platform Use Cordova view to embed PhoneGap into native applications to either transit smoothly to PhoneGap or incorporate PhoneGap functionalities Who This Book Is For If you are a mobile application developer in iOS or Android, or a web application developer who wants to learn how to make cross-platform mobile applications using PhoneGap, this book is perfect for you. To make the most of this book, it will be helpful if you have prior knowledge of HTML5, CSS, and JavaScript. What You Will Learn Get to grips with the fundamentals of PhoneGap to get started Set up a development environment for Linux, Mac OS, and Windows Use Cordova CLI, workflows, and Plugman Plugin manager to create mobile applications efficiently Understand the development workflow to create native cross-platform mobile applications Embed plugin support to transition to PhoneGap or use it to enhance existing applications Improve your mobile development knowledge using object-oriented programming (OOP), reusable components, and AJAX closures Be empowered to build your own mobile apps quickly with ease Discover tips and tricks to make app development fun and easy In Detail PhoneGap is an open source framework that allows you to quickly build cross-platform mobile apps using HTML5, JavaScript, and CSS. PhoneGap Build is a cloud service that allows you to quickly develop and compile mobile applications without SDKs, compilers, and hardware. PhoneGap allows you to use its existing plugins or create new ones, as per your requirements, to enhance your mobile applications. Starting by installing PhoneGap, you’ll develop an app that uses various device capabilities through different plugins and learn how to build an app in the cloud with PhoneGap’s Build service. You’ll discover how to use PhoneGap to create an application view, along with how to use a camera, geolocation, and other device capabilities to create engaging apps. Next, you’ll augment applications with PhoneGap's plugins using minimalistic code. You’ll explore the app preparation process to deploy your app to the app store. By the end of the book, you’ll have also learned how to apply hybrid mobile UIs that will work across different platforms and different screen sizes for better user experience. Style and approach This is an example-based, fast-paced guide that covers the fundamentals of creating cross-platform mobile applications with PhoneGap.

Harness the power of Redis to integrate and manage your projects efficiently About This Book Learn how to use Redis's data types efficiently to manage large data sets Scale Redis to multiple servers with Twemproxy, Redis Sentinel, and Redis Cluster A fast-paced guide, full of real-world examples to help you get the best out of the features offered by Redis Who This Book Is For If you are a competent developer with experience of working with data structure servers and want to boost your project's performance by learning about features of Redis, then this book is for you. What You Will Learn Build analytics applications using Bitmaps and Hyperloglogs Enhance scalability with Twemproxy, Redis Sentinel, and Redis Cluster Build a Time Series implementation in Node.js and Redis Create your own Redis commands by extending Redis with Lua Get to know security techniques to protect your data (SSL encryption, firewall rules, basic authorization) Persist data to disk and learn the trade-offs of AOF and RDB Understand how to use Node.js, PHP, Python, and Ruby clients for Redis Avoid common pitfalls when designing your next solution In Detail Redis is the most popular in-memory key-value data store. It’s very lightweight and its data types give it an edge over the other competitors. If you need an in-memory database or a high-performance cache system that is simple to use and highly scalable, Redis is what you need. Redis Essentials is a fast-paced guide that teaches the fundamentals on data types, explains how to manage data through commands, and shares experiences from big players in the industry. We start off by explaining the basics of Redis followed by the various data types such as Strings, hashes, lists, and more. Next, Common pitfalls for various scenarios are described, followed by solutions to ensure you do not fall into common traps. After this, major differences between client implementations in PHP, Python, and Ruby are presented. Next, you will learn how to extend Redis with Lua, get to know security techniques such as basic authorization, firewall rules, and SSL encryption, and discover how to use Twemproxy, Redis Sentinel, and Redis Cluster to scale infrastructures horizontally. At the end of this book, you will be able to utilize all the essential features of Redis to optimize your project's performance. Style and approach A practical guide that offers the foundation upon which you can begin to understand the capabilities of Redis using a step-by-step approach. This book is full of real-world problems and in-depth knowledge of the concepts and features of Redis, with plenty of examples.

Build, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of real-world applications with complete Scala code. A concise guide to processing large-scale networks with Apache Spark. Who This Book Is For This book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. Basic programming experience with Scala is assumed. Basic knowledge of Spark is assumed. What You Will Learn Write, build and deploy Spark applications with the Scala Build Tool. Build and analyze large-scale network datasets Analyze and transform graphs using RDD and graph-specific operations Implement new custom graph operations tailored to specific needs. Develop iterative and efficient graph algorithms using message aggregation and Pregel abstraction Extract subgraphs and use it to discover common clusters Analyze graph data and solve various data science problems using real-world datasets. In Detail Apache Spark is the next standard of open-source cluster-computing engine for processing big data. Many practical computing problems concern large graphs, like the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. Apache Spark GraphX API combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. This book will teach the user to do graphical programming in Apache Spark, apart from an explanation of the entire process of graphical data analysis. You will journey through the creation of graphs, its uses, its exploration and analysis and finally will also cover the conversion of graph elements into graph structures. This book begins with an introduction of the Spark system, its libraries and the Scala Build Tool. Using a hands-on approach, this book will quickly teach you how to install and leverage Spark interactively on the command line and in a standalone Scala program. Then, it presents all the methods for building Spark graphs using illustrative network datasets. Next, it will walk you through the process of exploring, visualizing and analyzing different network characteristics. This book will also teach you how to transform raw datasets into a usable form. In addition, you will learn powerful operations that can be used to transform graph elements and graph structures. Furthermore, this book also teaches how to create custom graph operations that are tailored for specific needs with efficiency in mind. The later chapters of this book cover more advanced topics such as clustering graphs, implementing graph-parallel iterative algorithms and learning methods from graph data. Style and approach A step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical examples that will ensure an overall understanding of the concepts of Spark.

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you’ll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Statistics, big data, and machine learning for Clojure programmers About This Book Write code using Clojure to harness the power of your data Discover the libraries and frameworks that will help you succeed A practical guide to understanding how the Clojure programming language can be used to derive insights from data Who This Book Is For This book is aimed at developers who are already productive in Clojure but who are overwhelmed by the breadth and depth of understanding required to be effective in the field of data science. Whether you’re tasked with delivering a specific analytics project or simply suspect that you could be deriving more value from your data, this book will inspire you with the opportunities–and inform you of the risks–that exist in data of all shapes and sizes. What You Will Learn Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with confidence Implement the core machine learning techniques of regression, classification, clustering and recommendation Understand the importance of the value of simple statistics and distributions in exploratory data analysis Scale algorithms to web-sized datasets efficiently using distributed programming models on Hadoop and Spark Apply suitable analytic approaches for text, graph, and time series data Interpret the terminology that you will encounter in technical papers Import libraries from other JVM languages such as Java and Scala Communicate your findings clearly and convincingly to nontechnical colleagues In Detail The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a *ing language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist’s diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you’ll see how to make use of Clojure’s Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don’t yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language’s flexibility! You’ll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark’s MapReduce and GraphX’s BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models. Above all, by following the explanations in this book, you’ll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future. Style and approach This is a practical guide to data science that teaches theory by example through the libraries and frameworks accessible from the Clojure programming language.