Over 70 recipes to get you writing powerful and efficient multithreaded, asynchronous, and parallel programs in C# 6.0 About This Book Rewritten and updated to take advantage of the latest C# 6 features Learn about multithreaded, asynchronous, and parallel programming through hands-on, code-first examples Use these recipes to build fast, scalable, and reliable applications in C# Who This Book Is For This book is aimed at those who are new to multithreaded programming, and who are looking for a quick and easy way to get started. It is assumed that you have some experience in C# and .NET already, and you should also be familiar with basic computer science terminology and basic algorithms and data structures. What You Will Learn Use C# 6.0 asynchronous language features Work with raw threads, synchronize threads, and coordinate their work Develop your own asynchronous API with Task Parallel Library Work effectively with a thread pool Scale up your server application with I/O threads Parallelize your LINQ queries with PLINQ Use common concurrent collections Apply different parallel programming patterns Use Reactive Extensions to run asynchronous operations and manage their options In Detail Multi-core processors are synonymous with computing speed and power in today’s world, which is why multithreading has become a key concern for C# developers. Multithreaded code helps you create effective, scalable, and responsive applications. This is an easy-to-follow guide that will show you difficult programming problems in context. You will learn how to solve them with practical, hands-on, recipes. With these recipes, you’ll be able to start creating your own scalable and reliable multithreaded applications. Starting from learning what a thread is, we guide you through the basics and then move on to more advanced concepts such as task parallel libraries, C# asynchronous functions, and much more. Rewritten to the latest C# specification, C# 6, and updated with new and modern recipes to help you make the most of the hardware you have available, this book will help you push the boundaries of what you thought possible in C#. Style and approach This is an easy-to-follow guide full of hands-on examples of real-world multithreading tasks. Each topic is explained and placed in context, and for the more inquisitive, there are also more in-depth details of the concepts used.

Over 80 recipes that will take your PHP 7 web development skills to the next level! About This Book This is the most up-to-date book in the market on PHP It covers the new features of version 7.x, best practices for server-side programming, and MVC frameworks The recipe-based approach will allow you to explore the unique capabilities that PHP offers to web programmers Who This Book Is For If you are an aspiring web developer, mobile developer, or backend programmer, then this book is for you as it will take your PHP programming skills to next level. Basic knowledge of PHP programming is assumed. What You Will Learn Use advanced PHP 7 features, such as the Abstract Syntax Tree, Uniform Variable Syntax, Scalar Type Hints, Generator Delegation, Anonymous Classes, and the Context Sensitive Lexer Discover where and when PHP 5 code needs to be re-written to avoid backwards-compatibility breaks Improve the overall application security and error handling by taking advantage of classes that implement the new throwable interface Solve practical real-world programming problems using PHP 7 Develop middle-wareclasses that allow PHP developers to gluedifferent open source libraries together seamlessly Define and Implement PSR-7 classes Create custom middleware using PSR-7 compliant classes Test and debug your code, and get to know the best practices In Detail PHP 7 comes with a myriad of new features and great tools to optimize your code and make your code perform faster than in previous versions. Most importantly, it allows you to maintain high traffic on your websites with low-cost hardware and servers through a multithreading web server. This book demonstrates intermediate to advanced PHP techniques with a focus on PHP 7. Each recipe is designed to solve practical, real-world problems faced by PHP developers like yourself every day. We also cover new ways of writing PHP code made possible only in version 7. In addition, we discuss backward-compatibility breaks and give you plenty of guidance on when and where PHP 5 code needs to be changed to produce the correct results when running under PHP 7. This book also incorporates the latest PHP 7.x features. By the end of the book, you will be equipped with the tools and skills required to deliver efficient applications for your websites and enterprises. Style and approach This book takes a recipe-based approach, with real-world examples that can serve as building blocks for a larger application. Each recipe is self-contained with no external dependencies. This book follows a problem-solution strategy so you understand how to deal with various scenarios you may encounter while using PHP 7 in your daily activities.

Build highly available and performant native web applications that seamlessly integrate with third-party APIs About This Book Get straight into the action with step-by-step recipes that show you how to put Service Workers to work Find out what Service Workers can do for your app, then do it! Get the first in-depth look at this important new feature for web developers Who This Book Is For Web developers, mobile application developers, and software engineers with any level of knowledge can use this book. You should be familiar with JavaScript and HTML. What You Will Learn Display a custom offline page Cache critical resources for offline use Implement offline Google Analytics Get network responses offline Implement push notifications Improve performance of your app In Detail It would be nice to have web apps that work offline and send push notifications. This is now possible with Service Workers, which can add native-like functionality to your web apps without requiring a download. This book will get your mobile and web apps functioning without Internet connectivity, improve performance and network interaction in order to increase the level of availability, and show you how to build performant applications that seamlessly integrate with third-party APIs. We’ll show you how to add Service Worker functionality to web apps and sites, access offline content through basic and advanced techniques, and build powerful interactive system notifications. We’ll also teach you about cache functionality and assets to provide immediate load even over narrow connections. We conclude by giving you various tips to improve app performance, including the background sync technique. By the end of this book, you’ll know build high performing and faster web and mobile applications with Service Workers. Style and approach This book provides lots of task-oriented, practical, and inspiring ways to put Service Workers to work. Step-by-step instructions will guide you through every task.

A handy reference guide for data analysts and data scientists to help to obtain value from big data analytics using Spark on Hadoop clusters About This Book This book is based on the latest 2.0 version of Apache Spark and 2.7 version of Hadoop integrated with most commonly used tools. Learn all Spark stack components including latest topics such as DataFrames, DataSets, GraphFrames, Structured Streaming, DataFrame based ML Pipelines and SparkR. Integrations with frameworks such as HDFS, YARN and tools such as Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall. Who This Book Is For Though this book is primarily aimed at data analysts and data scientists, it will also help architects, programmers, and practitioners. Knowledge of either Spark or Hadoop would be beneficial. It is assumed that you have basic programming background in Scala, Python, SQL, or R programming with basic Linux experience. Working experience within big data environments is not mandatory. What You Will Learn Find out and implement the tools and techniques of big data analytics using Spark on Hadoop clusters with wide variety of tools used with Spark and Hadoop Understand all the Hadoop and Spark ecosystem components Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Conventional and Structured Streaming, MLLib, ML Pipelines and Graphx See batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming Get to grips with data science and machine learning using MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall. In Detail Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data. Style and approach This step-by-step pragmatic guide will make life easy no matter what your level of experience. You will deep dive into Apache Spark on Hadoop clusters through ample exciting real-life examples. Practical tutorial explains data science in simple terms to help programmers and data analysts get started with Data Science

Take your penetration testing and IT security skills to a whole new level with the secrets of Metasploit About This Book Gain the skills to carry out penetration testing in complex and highly-secured environments Become a master using the Metasploit framework, develop exploits, and generate modules for a variety of real-world scenarios Get this completely updated edition with new useful methods and techniques to make your network robust and resilient Who This Book Is For This book is a hands-on guide to penetration testing using Metasploit and covers its complete development. It shows a number of techniques and methodologies that will help you master the Metasploit framework and explore approaches to carrying out advanced penetration testing in highly secured environments. What You Will Learn Develop advanced and sophisticated auxiliary modules Port exploits from PERL, Python, and many more programming languages Test services such as databases, SCADA, and many more Attack the client side with highly advanced techniques Test mobile and tablet devices with Metasploit Perform social engineering with Metasploit Simulate attacks on web servers and systems with Armitage GUI Script attacks in Armitage using CORTANA *ing In Detail Metasploit is a popular penetration testing framework that has one of the largest exploit databases around. This book will show you exactly how to prepare yourself against the attacks you will face every day by simulating real-world possibilities. We start by reminding you about the basic functionalities of Metasploit and its use in the most traditional ways. You’ll get to know about the basics of programming Metasploit modules as a refresher, and then dive into carrying out exploitation as well building and porting exploits of various kinds in Metasploit. In the next section, you’ll develop the ability to perform testing on various services such as SCADA, databases, IoT, mobile, tablets, and many more services. After this training, we jump into real-world sophisticated scenarios where performing penetration tests are a challenge. With real-life case studies, we take you on a journey through client-side attacks using Metasploit and various *s built on the Metasploit framework. By the end of the book, you will be trained specifically on time-saving techniques using Metasploit. Style and approach This is a step-by-step guide that provides great Metasploit framework methodologies. All the key concepts are explained details with the help of examples and demonstrations that will help you understand everything you need to know about Metasploit.

An in-depth guide to configuring NGINX for your everyday server needs About This Book Get tips, tricks, and master insight to help you configure NGINX for any server situation Integrate NGINX into your applications architecture with is, using hands-on guidance and practical code samples that are free to use Troubleshoot configuration problems before and as they arise, for a seamless NGINX server experience Who This Book Is For This book is for system administrators and engineers who want to personalize NGINX, and design a robust configuration module to solve their hosting problems. Some knowledge of NGINX is a plus, but is not a prerequisite. What You Will Learn Compile the right third-party module to meet your needs Write an authentication server to use with the mail proxy module Create your own SSL certificates to encrypt connections Use try_files to solve your file-existence check problems Cache and compress responses to get speedier user interaction Integrate popular PHP frameworks with the FastCGI module Construct useful logging configurations In Detail NGINX is a high-performance HTTP server and mail proxy designed to use very few system resources. But despite its power it is often a challenge to properly configure NGINX to meet your expectations. Mastering Nginx is the solution – an insider’s guide that will clarify the murky waters of NGINX’s configuration. Tune NGINX for various situations, improve your NGINX experience with some of the more obscure configuration directives, and discover how to design and personalize a configuration to match your needs. To begin with, quickly brush up on installing and setting up the NGINX server on the OS and its integration with third-party modules. From here, move on to explain NGINX's mail proxy module and its authentication, and reverse proxy to solve scaling issues. Then see how to integrate NGINX with your applications to perform tasks. The latter part of the book focuses on working through techniques to solve common web issues and the know-hows using NGINX modules. Finally, we will also explore different configurations that will help you troubleshoot NGINX server and assist with performance tuning. Style and approach This is a mastering guide where you will follow an instructional, conversational approach working through problems and their solutions.

Learn how to create more powerful data mining applications with this comprehensive Python guide to advance data analytics techniques About This Book Dive deeper into data mining with Python – don’t be complacent, sharpen your skills! From the most common elements of data mining to cutting-edge techniques, we’ve got you covered for any data-related challenge Become a more fluent and confident Python data-analyst, in full control of its extensive range of libraries Who This Book Is For This book is for data scientists who are already familiar with some basic data mining techniques such as SQL and machine learning, and who are comfortable with Python. If you are ready to learn some more advanced techniques in data mining in order to become a data mining expert, this is the book for you! What You Will Learn Explore techniques for finding frequent itemsets and association rules in large data sets Learn identification methods for entity matches across many different types of data Identify the basics of network mining and how to apply it to real-world data sets Discover methods for detecting the sentiment of text and for locating named entities in text Observe multiple techniques for automatically extracting summaries and generating topic models for text See how to use data mining to fix data anomalies and how to use machine learning to identify outliers in a data set In Detail Data mining is an integral part of the data science pipeline. It is the foundation of any successful data-driven strategy – without it, you'll never be able to uncover truly transformative insights. Since data is vital to just about every modern organization, it is worth taking the next step to unlock even greater value and more meaningful understanding. If you already know the fundamentals of data mining with Python, you are now ready to experiment with more interesting, advanced data analytics techniques using Python's easy-to-use interface and extensive range of libraries. In this book, you'll go deeper into many often overlooked areas of data mining, including association rule mining, entity matching, network mining, sentiment analysis, named entity recognition, text summarization, topic modeling, and anomaly detection. For each data mining technique, we'll review the state-of-the-art and current best practices before comparing a wide variety of strategies for solving each problem. We will then implement example solutions using real-world data from the domain of software engineering, and we will spend time learning how to understand and interpret the results we get. By the end of this book, you will have solid experience implementing some of the most interesting and relevant data mining techniques available today, and you will have achieved a greater fluency in the important field of Python data analytics. Style and approach This book will teach you the intricacies in applying data mining using real-world scenarios and will act as a very practical solution to your data mining needs.

Quick fixes to your common C# programming problems, with a focus on C# 6.0 About This Book Unique recipes for C#, that places it in its real-world context. You will be able to get yourself out of any coding-corner youve backed yourself into. All code samples available through GitHub to bring C#. In line with modern development workflows, written to the latest specification of C# 6.0. Who This Book Is For The book is aimed at developers who have basic familiarity with C# programming and will know the VS 2015 environment. What You Will Learn Write better and less code to achieve the same result as in previous versions of C#. Generate tests from the Code Contracts for mission critical methods. Integrate code in Visual Studio with GitHub. Create a web application in Azure. Design and build a microservice architecture Demystify the Rx library using Reactive extensions Write high performing codes in C# and understanding multi-threading. Security and Debugging. Implement Code Contracts on code in Visual Studio. In Detail During your application development workflow, there is always a moment when you need to get out of a tight spot. Through a recipe-based approach, this book will help you overcome common programming problems and get your applications ready to face the modern world. We start with C# 6, giving you hands-on experience with the new language features. Next, we work through the tasks that you perform on a daily basis such as working with strings, generics, and lots more. Gradually, we move on to more advanced topics such as the concept of object-oriented programming, asynchronous programming, reactive extensions, and code contracts. You will learn responsive high performance programming in C# and how to create applications with Azure. Next, we will review the choices available when choosing a source control solution. At the end of the book, we will show you how to create secure and robust code, and will help you ramp up your skills when using the new version of C# 6 and Visual Studio Style and Approach Unique recipe-based guide that will help you gain a solid understanding of the new concepts in C# 6 and Visual Studio Enterprise 2015 in a concise and technically correct manner.

Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Build effective applications by applying Odoo development best practices About This Book Each recipe stands by itself as much as possible, so that you can jump straight into the topics you prefer The recipes included cover all the major development areas of Odoo and the most important techniques explained through real-life projects From seasoned authors, learn the tricks of becoming a productive developer with the Odoo framework Who This Book Is For If you are a Python developer who wants to learn or consolidate your Odoo development skills, then this book is for you! Some experience with the JavaScript programming language and web development is required to fully benefit from the front-end chapters. What You Will Learn Install and manage Odoo environments and instances Use Models to define your application's data structures Add business logic to your applications Implement automated tests and debug Odoo apps Use back-end views to create a user interface Get to know about the access security model and internationalization features Develop front-end website features Extend the web client with new widgets and features In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source is also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. The book starts by covering Odoo installation and administration, and provides a gentle introduction to application development. It then dives deep into several of the areas that an experienced developer will need to use. You’ll learn implement business logic, adapt the UI, and extend existing features. Style and Approach These practical and easy-to-follow recipes are presented step-by-step, with dozens of hands-on recipes to boost your Odoo skills. This book can also be used as a reference guide for your daily work.

Get up to date with the finer points of Ubuntu Server using this comprehensive guide About This Book Get well-versed with newly-added features in Ubuntu 16.04 Master the art of installing, managing, and troubleshooting Ubuntu Server A practical easy-to-understand book that will help you enhance your existing skills. Who This Book Is For This book is intended for readers with intermediate or advanced-beginner skills with Linux, who would like to learn all about setting up servers with Ubuntu Server. This book assumes that the reader knows the basics of Linux, such as editing configuration files and running basic commands. What You Will Learn Learn how to manage users, groups, and permissions Encrypt and decrypt disks with Linux Unified Key Setup /Luks Setup SSH for remote access, and connect it to other nodes Understand how to add, remove, and search for packages Use NFS and Samba to share directories with other users Get to know techniques for managing Apache and MariaDB Explore best practices and troubleshooting techniques In Detail Ubuntu is a Debian-based Linux operating system, and has various versions targeted at servers, desktops, phones, tablets and televisions. The Ubuntu Server Edition, also called Ubuntu Server, offers support for several common configurations, and also simplifies common Linux server deployment processes. With this book as their guide, readers will be able to configure and deploy Ubuntu Servers using Ubuntu Server 16.04, with all the skills necessary to manage real servers. The book begins with the concept of user management, group management, as well as file-system permissions. To manage your storage on Ubuntu Server systems, you will learn how to add and format storage and view disk usage. Later, you will also learn how to configure network interfaces, manage IP addresses, deploy Network Manager in order to connect to networks, and manage network interfaces. Furthermore, you will understand how to start and stop services so that you can manage running processes on Linux servers. The book will then demonstrate how to access and share files to or from Ubuntu Servers. You will learn how to create and manage databases using MariaDB and share web content with Apache. To virtualize hosts and applications, you will be shown how to set up KVM/Qemu and Docker and manage virtual machines with virt-manager. Lastly, you will explore best practices and troubleshooting techniques when working with Ubuntu Servers. By the end of the book, you will be an expert Ubuntu Server user well-versed in its advanced concepts. Style and Approach This book is an advanced guide that will show readers how to administer, manage, and deploy Ubuntu server and will also provide expert-level knowledge on advanced security and backup techniques.

Take charge of SaltStack to automate and configure your enterprise-grade environments About This Book Automate tasks effectively and take charge of your infrastructure Effectively scale Salt to manage thousands of machines and tackle everyday problems Explore Salt’s inner workings and advance your knowledge of it Who This Book Is For This book is ideal for IT professionals and ops engineers who already manage groups of servers, but would like to expand their knowledge and gain expertise with SaltStack. This book explains the advanced features and concepts of Salt. A basic knowledge of Salt is required in order to get to grips with advanced Salt features. What You Will Learn Automate tasks effectively, so that your infrastructure can run itself Start building more complex concepts Master user-level internals Build scaling strategies Explore monitoring strategies Learn how to troubleshoot Salt and its subcomponents Explore best practices for Salt In Detail SaltStack is a powerful configuration management and automation suite designed to manage servers and tens of thousands of nodes. This book showcases Salt as a very powerful automation framework. We will review the fundamental concepts to get you in the right frame of mind, and then explore Salt in much greater depth. You will explore Salt SSH as a powerful tool and take Salt Cloud to the next level. Next, you’ll master using Salt services with ease in your infrastructure. You will discover methods and strategies to scale your infrastructure properly. You will also learn how to use Salt as a powerful monitoring tool. By the end of this book, you will have learned troubleshooting tips and best practices to make the entire process of using Salt pain-free and easy. Style and approach This book follows a step-by-step conversational tone. Topics are covered in detail through examples and a user-friendly approach.

Unleash the power and flexibility of the Bayesian framework About This Book Simplify the Bayes process for solving complex statistical problems using Python; Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems and practice exercises; Learn how and when to use Bayesian analysis in your applications with this guide. Who This Book Is For Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to day projects. Programming experience with Python is essential. No previous statistical knowledge is assumed. What You Will Learn Understand the essentials Bayesian concepts from a practical point of view Learn how to build probabilistic models using the Python library PyMC3 Acquire the skills to sanity-check your models and modify them if necessary Add structure to your models and get the advantages of hierarchical models Find out how different models can be used to answer different data analysis questions When in doubt, learn to choose between alternative models. Predict continuous target outcomes using regression analysis or assign classes using logistic and softmax regression. Learn how to think probabilistically and unleash the power and flexibility of the Bayesian framework In Detail The purpose of this book is to teach the main concepts of Bayesian data analysis. We will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, we will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. We will also look into mixture models and clustering data, and we will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems. Style and approach Bayes algorithms are widely used in statistics, machine learning, artificial intelligence, and data mining. This will be a practical guide allowing the readers to use Bayesian methods for statistical modelling and analysis using Python.

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This Book ?Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow ?Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ?Real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ?Learn about machine learning landscapes along with the historical development and progress of deep learning ?Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x ?Access public datasets and utilize them using TensorFlow to load, process, and transform data ?Use TensorFlow on real-world datasets, including images, text, and more ?Learn how to evaluate the performance of your deep learning models ?Using deep learning for scalable object detection and mobile computing ?Train machines quickly to learn from data by exploring reinforcement learning techniques ?Explore active areas of deep learning research and applications

Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecma* 6 and Type*

Writing concurrent and parallel programming applications is an integral skill for any Java programmer. Java 9 comes with a host of fantastic features, including significant performance improvements and new APIs. This book will take you through all the new APIs, showing you how to build parallel and multi-threaded applications. The book covers all the elements of the Java Concurrency API, with essential recipes that will help you take advantage of the exciting new capabilities. You will learn how to use parallel and reactive streams to process massive data sets. Next, you will move on to create streams and use all their intermediate and terminal operations to process big collections of data in a parallel and functional way. Further, you ll discover a whole range of recipes for almost everything, such as thread management, synchronization, executors, parallel and reactive streams, and many more. At the end of the book, you will learn how to obtain information about the status of some of the most useful components of the Java Concurrency API and how to test concurrent applications using different tools. What you will learn ?Find out to manage the basic components of the Java Concurrency API ?Use synchronization mechanisms to avoid data race conditions and other problems of concurrent applications ?Separate the thread management from the rest of the application with the Executor framework ?Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework ?Process massive data sets in an optimized way using streams and reactive streams ?See which data structures we can use in concurrent applications and how to use them ?Practice efficient techniques to test concurrent applications ?Get to know tips and tricks to design concurrent applications

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks. What you will learn ?Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm ?Fine-tune a neural network to improve the quality of results ?Use deep learning for image and audio processing ?Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases ?Identify problems

Work through recipes to unlock the full potential of the next generation graphics API―Vulkan About This Book ?This book explores a wide range of modern graphics programming techniques and GPU compute methods to make the best use of the Vulkan API ?Learn techniques that can be applied to a wide range of platforms desktop, smartphones, and embedded devices Who This Book Is For This book is ideal for developers who know C/C++ languages, have some basic familiarity with graphics programming, and now want to take advantage of the new Vulkan API in the process of building next generation computer graphics. Some basic familiarity of Vulkan would be useful to follow the recipes. OpenGL developers who want to take advantage of the Vulkan API will also find this book useful. What You Will Learn?Work with Swapchain to present images on screen ?Create, submit, and synchronize operations processed by the hardware ?Create buffers and images, manage their memory, and upload data to them from CPU ?Explore de*or sets and set up an interface between application and shaders ?Organize drawing operations into a set of render passes and subpasses ?Prepare graphics pipelines to draw 3D scenes and compute pipelines to perform mathematical calculations ?Implement geometry projection and tessellation, texturing, lighting, and post-processing techniques ?Write shaders in GLSL and convert them into SPIR-V assemblies ?Find out about and

"Key Features ?Get to the grips with the latest version of Apache Spark ?Utilize Spark's machine learning library to implement predictive analytics ?Leverage Spark's powerful tools to load, analyze, clean, and transform your data Book De*ion Spark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression. 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. What you will learn ?Get hands-on with the latest version of Spark ML ?Create your first Spark program with Scala and Python ?Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 ?Access public machine learning datasets and use Spark to load, process, clean, and transform data ?Use Spark's machine learning library to implement programs by utilizing well-known machine learning models ?Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models ?Write Spark functions to evaluate the performance of your machine learning models "

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data. What you will learn ?Get to know how to measure geographic distributions ?Perform clustering analysis including hot spot and outlier analysis ?Conduct data conversion tasks using the Utilities toolset ?Understand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics Toolbox ?Get to grips with the basics of R for performing spatial statistical programming ?Create custom ArcGIS tools with R and ArcGIS Bridge ?Understand the application of Spatial Statistics tools

Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. What you will learn ?Get a solid understanding of the data processing toolbox available in Java ?Explore the data science ecosystem available in Java