Get to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python. Key Features * Get a hands-on, fast-paced introduction to the Python data science stack * Explore ways to create useful metrics and statistics from large datasets * Create detailed analysis reports with real-world data Book Description Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems. The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools. By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs. What you will learn * Use Python to read and transform data into different formats * Generate basic statistics and metrics using data on disk * Work with computing tasks distributed over a cluster * Convert data from various sources into storage or querying formats * Prepare data for statistical analysis, visualization, and machine learning * Present data in the form of effective visuals Who this book is for Big Data Analysis with Python is designed for Python developers, data analysts, and data scientists who want to get hands-on with methods to control data and transform it into impactful insights. Basic knowledge of statistical measurements and relational databases will help you to understand various concepts explained in this book.

Explore the different data mining techniques using the libraries and packages offered by Python Key Features * Grasp the basics of data loading, cleaning, analysis, and visualization * Use the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data mining * Your one-stop guide to build efficient data mining pipelines without going into too much theory Book Description Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining. This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle. What you will learn * Explore the methods for summarizing datasets and visualizing/plotting data * Collect and format data for analytical work * Assign data points into groups and visualize clustering patterns * Learn how to predict continuous and categorical outputs for data * Clean, filter noise from, and reduce the dimensions of data * Serialize a data processing model using scikit-learn’s pipeline feature * Deploy the data processing model using Python’s pickle module Who this book is for Python developers interested in getting started with data mining will love this book. Budding data scientists and data analysts looking to quickly get to grips with practical data mining with Python will also find this book to be useful. Knowledge of Python programming is all you need to get started.

Manipulate and analyze network data with the power of Python and NetworkX Key Features * Understand the terminology and basic concepts of network science * Leverage the power of Python and NetworkX to represent data as a network * Apply common techniques for working with network data of varying sizes Book Description NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use. If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts. By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems. What you will learn * Use Python and NetworkX to analyze the properties of individuals and relationships * Encode data in network nodes and edges using NetworkX * Manipulate, store, and summarize data in network nodes and edges * Visualize a network using circular, directed and shell layouts * Find out how simulating behavior on networks can give insights into real-world problems * Understand the ongoing impact of network science on society, and its ethical considerations Who this book is for If you are a programmer or data scientist who wants to manipulate and analyze network data in Python, this book is perfect for you. Although prior knowledge of network science is not necessary, some Python programming experience will help you understand the concepts covered in the book easily.

Concepts, tools, and techniques to explore deep learning architectures and methodologies Key Features * Explore advanced deep learning architectures using various datasets and frameworks * Implement deep architectures for neural network models such as CNN, RNN, GAN, and many more * Discover design patterns and different challenges for various deep learning architectures Book Description Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and implement deep learning architectures to resolve various deep learning research problems. Hands-On Deep Learning Architectures with Python explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations and ideas to help you build efficient artificial intelligence systems (AI), this book will help you learn how neural networks play a major role in building deep architectures. You will understand various deep learning architectures (such as AlexNet, VGG Net, GoogleNet) with easy-to-follow code and diagrams. In addition to this, the book will also guide you in building and training various deep architectures such as the Boltzmann mechanism, autoencoders, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), GAN, and more—all with practical implementations. By the end of this book, you will be able to construct deep models using popular frameworks and datasets with the required design patterns for each architecture. You will be ready to explore the potential of deep architectures in today's world. What you will learn * Implement CNNs, RNNs, and other commonly used architectures with Python * Explore architectures such as VGGNet, AlexNet, and GoogLeNet * Build deep learning architectures for AI applications such as face and image recognition, fraud detection, and many more * Understand the architectures and applications of Boltzmann machines and autoencoders with concrete examples * Master artificial intelligence and neural network concepts and apply them to your architecture * Understand deep learning architectures for mobile and embedded systems Who this book is for If you’re a data scientist, machine learning developer/engineer, or deep learning practitioner, or are curious about AI and want to upgrade your knowledge of various deep learning architectures, this book will appeal to you. You are expected to have some knowledge of statistics and machine learning algorithms to get the best out of this book

This book is for web developers and designers who work with HTML and JavaScript to help them manage data and interactivity with data using KnockoutJS. Knowledge about jQuery will be useful but is not necessary.

This book employs an incremental, step-by-step approach to get you familiarized with everything from the basic terms, board components, and development environments to developing real projects. Each project will demonstrate how to use specific board components and tools. Both Galileo and Galileo Gen 2 are covered in this book.

This book is useful for Hadoop administrators who need to learn how to monitor and diagnose their clusters. Also, the book will prove useful for new users of the technology, as the language used is simple and easy to grasp.

A playful, informal approach to using the Raspberry Pi for mischief! Raspberry Pi for Secret Agents is for all mischievous Raspberry Pi owners who’d like to see their computer transform into a neat spy gadget to be used in a series of practical pranks and projects. No previous skills are required to follow along and if you’re completely new to Linux, you’ll pick up much of the basics for free. Apart from the Raspberry Pi board itself, a USB microphone and/or a webcam is required for most of the audio/video topics and a Wi-Fi dongle is recommended for the networking examples. A Windows/Mac OS X/Linux computer (or second Raspberry Pi) is also recommended for remote network access.

This book is for Node.js developers who want a more in-depth knowledge of the platform to improve the performance of their applications. Whether you have a base Node.js background or you are an expert who knows the garbage collector and wants to leverage it to make applications more robust, the examples in this book will benefit you.

Written with an example-based approach, Building UIs with Wijmo leads you step by step through the implementation and customization of each library component and its associated resources. Reference tables of each configuration option, method, and event for each component are provided, alongside detailed explanations of how each widget is used.Building UIs with Wijmo is targeted at readers who are familiar with HTML, CSS, JavaScript, and jQuery, and have a basic understanding of web development. Although knowledge of jQuery UI is not mandatory, it would be a bonus as it is quite similar to Wijmo. Only the last chapter of the book on extending Wijmo requires advanced CSS and JavaScript knowledge.

Written in an easy-to-follow step-by-step format, you will be able to get started in next to no time with minimal effort and zero fuss.BackTrack: Testing Wireless Network Security is for anyone who has an interest in security and who wants to know more about wireless networks.All you need is some experience with networks and computers and you will be ready to go.

It is a tutorial guide to learning how to use Opa with JavaScript, Nodejs, and MongoDB to develop web applications easily and effectively.If you are a web developer who wants to get started with the Opa framework and build web applications with itThen this book is for you. Web development experience is assumed and would be helpful.

This book is intended for .NET developers who want to use the MVVM design pattern to create powerful client-side JavaScript linked to server-side C# logic. Basic experience with ASP.NET, Razor, and creating web applications is needed.

Drupal 8 Configuration Management is intended for people who use Drupal 8 to build websites, whether you are a hobbyist using Drupal for the first time, a long-time Drupal site builder, or a professional web developer.

Android Application Development with Maven is intended for Android developers or devops engineers who want to use Maven to effectively develop quality Android applications. It would be helpful, but not necessary, if you have some previous experience with Maven.

This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.

A practical book with plenty of screenshots to guide you through the many features of multilingual Drupal. A demo ecommerce site is provided if you want to practice on a sample site, although you can apply the techniques learnt in the book directly to your site too. Any Drupal users who know the basics of building a Drupal site and are familiar with the Drupal UI, will benefit from this book. No previous knowledge of localization or internationalization is required.

A practical book with plenty of step-by-step instructions and informative screenshots to guide you through the many features of gradebook. Moodle Gradebook is for anyone who uses Moodle as a course instructor. You will need to know the basic functions of using and navigating Moodle, but no prior knowledge of the grades functions will be required.

Adobe Edge Quickstart Guide is a practical guide on creating engaging content for the Web with Adobe's newest HTML5 tool. By taking a chapter-by-chapter look at each major aspect of Adobe Edge, the book lets you digest the available features in small, easily understandable chunks, allowing you to start using Adobe Edge for your web design needs immediately. If you are interested in creating engaging motion and interactive compositions using web standards with professional tooling, then this book is for you. Those with a background in Flash Professional wanting to get started quickly with Adobe Edge will also find this book useful.

This is a problem-solution approach to take your FreeSWITCH skills to the next level, where everything is explained in a practical way. If you are a system administrator, hobbyist, or someone who uses FreeSWITCH on a regular basis, this book is for you. Whether you are a FreeSWITCH expert or just getting started, this book will take your skills to the next level.

This book is for programmers and developers who want to improve the performance of their R programs by making them run faster with large data sets or who are trying to solve a pesky performance problem.