Learn and implement various Quantitative Finance concepts using the popular Python libraries About This Book ? Understand the fundamentals of Python data structures and work with time-series data ? Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib ? A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance Who This Book Is For This book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data. What You Will Learn ? Become acquainted with Python in the first two chapters ? Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models ? Learn how to price a call, put, and several exotic options ? Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options ? Understand the concept of volatility and how to test the hypothesis that volatility changes over the years ? Understand the ARCH and GARCH processes and how to write related Python programs In Detail This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option. Style and approach This book takes a step-by-step approach in explaining the libraries and modules in Python, and how they can be used to implement various aspects of quantitative finance. Each concept is explained in depth and supplemented with code examples for better understanding.

Build consistent web apps with Redux by easily centralizing the state of your application. About This Book ? Write applications that behave consistently, run in different environments (client, server and native), and are easy to test ? Take your web apps to the next level by combining the power of Redux with other frameworks such as React and Angular ? Uncover the best practices and hidden features of Redux to build applications that are powerful, consistent, and maintainable Who This Book Is For This book targets developers who are already fluent in JavaScript but want to extend their web development skills to develop and maintain bigger applications. What You Will Learn ? Understand why and how Redux works ? Implement the basic elements of Redux ? Use Redux in combination with React/Angular to develop a web application ? Debug a Redux application ? Interface with external APIs with Redux ? Implement user authentication with Redux ? Write tests for all elements of a Redux application ? Implement simple and more advanced routing with Redux ? Learn about server-side rendering with Redux and React ? Create higher-order reducers for Redux ? Extend the Redux store via middleware In Detail The book starts with a short introduction to the principles and the ecosystem of Redux, then moves on to show how to implement the basic elements of Redux and put them together. Afterward, you are going to learn how to integrate Redux with other frameworks, such as React and Angular. Along the way, you are going to develop a blog application. To practice developing growing applications with Redux, we are going to start from nothing and keep adding features to our application throughout the book. You are going to learn how to integrate and use Redux DevTools to debug applications, and access external APIs with Redux. You are also going to get acquainted with writing tests for all elements of a Redux application. Furthermore, we are going to cover important concepts in web development, such as routing, user authentication, and communication with a backend server After explaining how to use Redux and how powerful its ecosystem can be, the book teaches you how to make your own abstractions on top of Redux, such as higher-order reducers and middleware. By the end of the book, you are going to be able to develop and maintain Redux applications with ease. In addition to learning about Redux, you are going be familiar with its ecosystem, and learn a lot about JavaScript itself, including best practices and patterns. Style and approach This practical guide will teach you how to develop a complex, data-intensive application leveraging the capabilities of the Redux framework.

This step-by-step guide demonstrates how to build simple-to-advanced applications through examples in R using modern tools. About This Book ? Get a firm hold on the fundamentals of R through practical hands-on examples ? Get started with good R programming fundamentals for data science ? Exploit the different libraries of R to build interesting applications in R Who This Book Is For This books is for aspiring data science professionals or statisticians who would like to learn about the R programming language in a practical manner. Basic programming knowledge is assumed. What You Will Learn ? Discover techniques to leverage R’s features, and work with packages ? Perform a de*ive analysis and work with statistical models using R ? Work efficiently with objects without using loops ? Create diverse visualizations to gain better understanding of the data ? Understand ways to produce good visualizations and create reports for the results ? Read and write data from relational databases and REST APIs, both packaged and unpackaged ? Improve performance by writing better code, delegating that code to a more efficient programming language, or making it parallel In Detail R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable. Style and Approach This is an easy-to-understand guide filled with real-world examples, giving you a holistic view of R and practical, hands-on experience.

Develop your first interactive 2D and 3D platformer game by learning the fundamentals of C# About This Book ? This is a step-by-step guide to learn the fundamentals of C# 7 *ing to develop GameObjects and master the basics of the new UI system in Unity ? Build and develop your 2D game right from scratch while implementing the principles of object-oriented programming and coding in C# 7 ? Get to grips with the fundamentals of optimizing your game using the latest features of Unity 2017 Who This Book Is For The book is targeted at beginner level Unity developers with no programming experience. If you are a Unity developer and you wish to learn how to write C# *s and code by creating games, then this book is for you. What You Will Learn ? Learn C# 7 using new features like tuples, variables, and non-nullable reference types while building games ? Understand the fundamentals of variables, methods, and code syntax in C# ? Use loops and collections efficiently in Unity to reduce the amount of code ? Develop a game using the object-oriented programming principles ? Implement simple enemy characters into the game to learn point to point movement and Tree behaviors ? Avoid performance mistakes by implementing different optimization techniques ? Export 3D models and 3D animations and import them inside a Unity project ? With your new knowledge of coding, you will be able to look at Unity's Scripting Reference code examples with confidence In Detail With the latest version of Unity 2017 released, are you interested in developing creative and interactive games while learning C# alongside? Then this is the book that you are looking for. Its all about offering you a fun introduction to the world of game programming with C#. You’ll start with the basics to get started with C# 7 and its latest features. Then you’ll see how to use C# 7 and its latest functional programming capabilities to create amazing games with Unity 2017. You’ll create your first C# * for Unity, add objects into it, and learn how to create game elements with them. Then you’ll work with the latest functional programming features of C# and how to leverage them for great game *ing. Throughout the book, you’ll learn to use the new Unity 2017 2D tool set and create an interactive 2D game with it. You will make enemies appear to challenge your player, and go through some optimization techniques to ensure great game performance. At the end, your 2D game will be transformed into 3D, and you’ll be able to skill up to become a pro C# programmer with Unity 2017! Style and approach The book takes a practical, step-by-step approach where you learn C# coding while developing fun and interactive games.

Learn the fundamentals of vue.js by creating complex SPAs with Vuex, vue-router and more About This Book ? We bridge the gap between "learning" and "doing" by providing real-world examples that will improve your web development skills with Vue.js ? Explore the exciting features of Vue.js 2 through practical and interesting examples ? Explore modern development tools and learn how to utilize them by building applications with Vue.js Who This Book Is For This book is for developers who know the basics of JavaScript and are looking to learn Vue.js with real examples. You should understand the basics of JavaScript functions and variables and be comfortable with using CSS or a CSS framework for styling your projects. What You Will Learn ? Looping through data with Vue.js ? Searching and filtering data ? Using components to display data ? Getting a list of files using the dropbox API ? Navigating through a file tree and loading folders from a URL ? Caching with Vuex ? Pre-caching for faster navigation ? Introducing vue-router and loading components ? Using vue-router dynamic routes to load data ? Using vue-router and Vuex to create an ecommerce store In Detail Vue.js is a frontend web framework which makes it easy to do just about anything, from displaying data up to creating full-blown web apps, and has become a leading tool for web developers. This book puts Vue.js into a real-world context, guiding you through example projects that helps you build Vue.js applications from scratch. With this book, you will learn how to use Vue.js by creating three Single Page web applications. Throughout this book, we will cover the usage of Vue, for building web interfaces, Vuex, an official Vue plugin which makes caching and storing data easier, and Vue-router, a plugin for creating routes and URLs for your application. Starting with a JSON dataset, the first part of the book covers Vue objects and how to utilize each one. This will be covered by exploring different ways of displaying data from a JSON dataset. We will then move on to manipulating the data with filters and search and creating dynamic values. Next, you will see how easy it is to integrate remote data into an application by learning how to use the Dropbox API to display your Dropbox contents in an application In the final section, you will see how to build a product catalog and dynamic shopping cart using the Vue-router, giving you the building blocks of an e-commerce store. Style and approach This book takes you three projects, with step-by-step instructions to help you understand the concepts of Vue and put it into practice.

Learn the basics of Geographic Information Systems by solving real-world problems with powerful open source tools About This Book ? This easy-to-follow guide allows you to manage and analyze geographic data with ease using open source tools ? Publish your geographical data online ? Learn the basics of geoinformatics in a practical way by solving problems Who This Book Is For The book is for IT professionals who have little or no knowledge of GIS. It’s also useful for those who are new to the GIS field who don’t want to spend a lot of money buying licenses of commercial tools and training. What You Will Learn ? Collect GIS data for your needs ? Store the data in a PostGIS database ? Exploit the data using the power of the GIS queries ? Analyze the data with basic and more advanced GIS tools ? Publish your data and share it with others ? Build a web map with your published data In Detail The most commonly used GIS tools automate tasks that were historically done manually—compiling new maps by overlaying one on top of the other or physically cutting maps into pieces representing specific study areas, changing their projection, and getting meaningful results from the various layers by applying mathematical functions and operations. This book is an easy-to-follow guide to use the most matured open source GIS tools for these tasks. We’ll start by setting up the environment for the tools we use in the book. Then you will learn how to work with QGIS in order to generate useful spatial data. You will get to know the basics of queries, data management, and geoprocessing. After that, you will start to practice your knowledge on real-world examples. We will solve various types of geospatial analyses with various methods. We will start with basic GIS problems by imitating the work of an enthusiastic real estate agent, and continue with more advanced, but typical tasks by solving a decision problem. Finally, you will find out how to publish your data (and results) on the web. We will publish our data with QGIS Server and GeoServer, and create a basic web map with the API of the lightweight Leaflet web mapping library. Style and approach The book guides you step by step through each of the core concepts of the GIS toolkit, building an overall picture of its capabilities. This guide approaches the topic systematically, allowing you to build upon what you learned in previous chapters. By the end of this book, you’ll have an understanding of the aspects of building a GIS system and will be able to take that knowledge with you to whatever project calls for it.

Become an expert in implementing advanced, network-related tasks with Python. About This Book ? Build the skills to perform all networking tasks using Python with ease ? Use Python for network device automation, DevOps, and software-defined networking ? Get practical guidance to networking with Python Who This Book Is For If you are a network engineer or a programmer who wants to use Python for networking, then this book is for you. A basic familiarity with networking-related concepts such as TCP/IP and a familiarity with Python programming will be useful. What You Will Learn ? Review all the fundamentals of Python and the TCP/IP suite ? Use Python to execute commands when the device does not support the API or programmatic interaction with the device ? Implement automation techniques by integrating Python with Cisco, Juniper, and Arista eAPI ? Integrate Ansible using Python to control Cisco, Juniper, and Arista networks ? Achieve network security with Python ? Build Flask-based web-service APIs with Python ? Construct a Python-based migration plan from a legacy to scalable SDN-based network. In Detail This book begins with a review of the TCP/ IP protocol suite and a refresher of the core elements of the Python language. Next, you will start using Python and supported libraries to automate network tasks from the current major network vendors. We will look at automating traditional network devices based on the command-line interface, as well as newer devices with API support, with hands-on labs. We will then learn the concepts and practical use cases of the Ansible framework in order to achieve your network goals. We will then move on to using Python for DevOps, starting with using open source tools to test, secure, and analyze your network. Then, we will focus on network monitoring and visualization. We will learn how to retrieve network information using a polling mechanism, ?ow-based monitoring, and visualizing the data programmatically. Next, we will learn how to use the Python framework to build your own customized network web services. In the last module, you will use Python for SDN, where you will use a Python-based controller with OpenFlow in a hands-on lab to learn its concepts and applications. We will compare and contrast OpenFlow, OpenStack, OpenDaylight, and NFV. Finally, you will use everything you’ve learned in the book to construct a migration plan to go from a legacy to a scalable SDN-based network. Style and approach An easy-to-follow guide packed with hands-on examples of using Python for network device automation, DevOps, and SDN.

Over 90 recipes that leverage the powerful features of the Standard Library in C++17 About This Book ? Learn the latest features of C++ and how to write better code by using the Standard Library (STL). Reduce the development time for your applications. ? Understand the scope and power of STL features to deal with real-world problems. ? Compose your own algorithms without forfeiting the simplicity and elegance of the STL way. Who This Book Is For This book is for intermediate-to-advanced C++ programmers who want to get the most out of the Standard Template Library of the newest version of C++: C++ 17. What You Will Learn ? Learn about the new core language features and the problems they were intended to solve ? Understand the inner workings and requirements of iterators by implementing them ? Explore algorithms, functional programming style, and lambda expressions ? Leverage the rich, portable, fast, and well-tested set of well-designed algorithms provided in the STL ? Work with strings the STL way instead of handcrafting C-style code ? Understand standard support classes for concurrency and synchronization, and how to put them to work ? Use the filesystem library addition available with the C++17 STL In Detail C++ has come a long way and is in use in every area of the industry. Fast, efficient, and flexible, it is used to solve many problems. The upcoming version of C++ will see programmers change the way they code. If you want to grasp the practical usefulness of the C++17 STL in order to write smarter, fully portable code, then this book is for you. Beginning with new language features, this book will help you understand the language’s mechanics and library features, and offers insight into how they work. Unlike other books, ours takes an implementation-specific, problem-solution approach that will help you quickly overcome hurdles. You will learn the core STL concepts, such as containers, algorithms, utility classes, lambda expressions, iterators, and more, while working on practical real-world recipes. These recipes will help you get the most from the STL and show you how to program in a better way. By the end of the book, you will be up to date with the latest C++17 features and save time and effort while solving tasks elegantly using the STL. Style and approach This recipe-based guide will show you how to make the best use of C++ together with the STL to squeeze more out of the standard language

Discover practical solutions for a wide range of real-world network programming tasks About This Book ? Solve real-world tasks in the area of network programming, system/networking administration, network monitoring, and more. ? Familiarize yourself with the fundamentals and functionalities of SDN ? Improve your skills to become the next-gen network engineer by learning the various facets of Python programming Who This Book Is For This book is for network engineers, system/network administrators, network programmers, and even web application developers who want to solve everyday network-related problems. If you are a novice, you will develop an understanding of the concepts as you progress with this book. What You Will Learn ? Develop TCP/IP networking client/server applications ? Administer local machines' IPv4/IPv6 network interfaces ? Write multi-purpose efficient web clients for HTTP and HTTPS protocols ? Perform remote system administration tasks over Telnet and SSH connections ? Interact with popular websites via web services such as XML-RPC, SOAP, and REST APIs ? Monitor and analyze major common network security vulnerabilities ? Develop Software-Defined Networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX Controllers ? Emulate simple and complex networks with Mininet and its extensions for network and systems emulations ? Learn to configure and build network systems and Virtual Network Functions (VNF) in heterogeneous deployment environments ? Explore various Python modules to program the Internet In Detail Python Network Programming Cookbook - Second Edition highlights the major aspects of network programming in Python, starting from writing simple networking clients to developing and deploying complex Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) systems. It creates the building blocks for many practical web and networking applications that rely on various networking protocols. It presents the power and beauty of Python to solve numerous real-world tasks in the area of network programming, network and system administration, network monitoring, and web-application development. In this edition, you will also be introduced to network modelling to build your own cloud network. You will learn about the concepts and fundamentals of SDN and then extend your network with Mininet. Next, you’ll find recipes on Authentication, Authorization, and Accounting (AAA) and open and proprietary SDN approaches and frameworks. You will also learn to configure the Linux Foundation networking ecosystem and deploy and automate your networks with Python in the cloud and the Internet scale. By the end of this book, you will be able to analyze your network security vulnerabilities using advanced network packet capture and analysis techniques. Style and approach This book follows a practical approach and covers major aspects of network programming in Python. It provides hands-on recipes combined with short and concise explanations on code snippets. This book will serve as a supplementary material to develop hands-on skills in any academic course on network programming. This book further elaborates network softwarization, including Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and orchestration. We learn to configure and deploy enterprise network platforms, develop applications on top of them with Python.

Apply Functional Programming techniques to C++ to build highly modular, testable, and reusable code About This Book ? Modularize your applications and make them highly reusable and testable ? Get familiar with complex concepts such as metaprogramming, concurrency, and immutability ? A highly practical guide to building functional code in C++ filled with lots of examples and real-world use cases Who This Book Is For This book is for C++ developers comfortable with OOP who are interested in learning how to apply the functional paradigm to create robust and testable apps. What You Will Learn ? Get to know the difference between imperative and functional approaches ? See the use of first-class functions and pure functions in a functional style ? Discover various techniques to apply immutable state to avoid side effects ? Design a recursive algorithm effectively ? Create faster programs using lazy evaluation ? Structure code using design patterns to make the design process easier ? Use concurrency techniques to develop responsive software ? Learn how to use the C++ Standard Template Library and metaprogramming in a functional way to improve code optimization In Detail Functional programming allows developers to divide programs into smaller, reusable components that ease the creation, testing, and maintenance of software as a whole. Combined with the power of C++, you can develop robust and scalable applications that fulfill modern day software requirements. This book will help you discover all the C++ 17 features that can be applied to build software in a functional way. The book is divided into three modules—the first introduces the fundamentals of functional programming and how it is supported by modern C++. The second module explains how to efficiently implement C++ features such as pure functions and immutable states to build robust applications. The last module describes how to achieve concurrency and apply design patterns to enhance your application’s performance. Here, you will also learn to optimize code using metaprogramming in a functional way. By the end of the book, you will be familiar with the functional approach of programming and will be able to use these techniques on a daily basis. Style and approach This book uses a module-based approach, where each module will cover important aspects of functional programming in C++ and will help you develop efficient and robust applications through gaining a practical understanding.

Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book ? Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more ? Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka ? An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn ? Understand the core concepts of Apache Storm and real-time processing ? Follow the steps to deploy multiple nodes of Storm Cluster ? Create Trident topologies to support various message-processing semantics ? Make your cluster sharing effective using Storm scheduling ? Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more ? Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.

Extract patterns and knowledge from your data in easy way using MATLAB About This Book ? Get your first steps into machine learning with the help of this easy-to-follow guide ? Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB ? Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn ? Learn the introductory concepts of machine learning. ? Discover different ways to transform data using SAS XPORT, import and export tools, ? Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. ? Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. ? Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. ? Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. ? Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book ? Process and analyze big data in a distributed and scalable way ? Write sophisticated Spark pipelines that incorporate elaborate extraction ? Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn ? Use Spark streams to cluster tweets online ? Run the PageRank algorithm to compute user influence ? Perform complex manipulation of DataFrames using Spark ? Define Spark pipelines to compose individual data transformations ? Utilize generated models for off-line/on-line prediction ? Transfer the learning from an ensemble to a simpler Neural Network ? Understand basic graph properties and important graph operations ? Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language ? Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.

Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book ? Load, store, edit, and visualize data using OpenCV and Python ? Grasp the fundamental concepts of classification, regression, and clustering ? Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide ? Evaluate, compare, and choose the right algorithm for any task Who This Book Is For This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks. What You Will Learn ? Explore and make effective use of OpenCV's machine learning module ? Learn deep learning for computer vision with Python ? Master linear regression and regularization techniques ? Classify objects such as flower species, handwritten digits, and pedestrians ? Explore the effective use of support vector machines, boosted decision trees, and random forests ? Get acquainted with neural networks and Deep Learning to address real-world problems ? Discover hidden structures in your data using k-means clustering ? Get to grips with data pre-processing and feature engineering In Detail Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google’s DeepMind. OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for. Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch! Style and approach OpenCV machine learning connects the fundamental theoretical principles behind machine learning to their practical applications in a way that focuses on asking and answering the right questions. This book walks you through the key elements of OpenCV and its powerful machine learning classes, while demonstrating how to get to grips with a range of models.

Master the principles to make applications robust, scalable and responsive About This Book ? Implement concurrent applications using the Java 9 Concurrency API and its new components ? Improve the performance of your applications and process more data at the same time, taking advantage of all of your resources ? Construct real-world examples related to machine learning, data mining, natural language processing, and more Who This Book Is For This book is for competent Java developers who have basic understanding of concurrency, but knowledge of effective implementation of concurrent programs or usage of streams for making processes more efficient is not required What You Will Learn ? Master the principles that every concurrent application must follow ? See how to parallelize a sequential algorithm to obtain better performance without data inconsistencies and deadlocks ? Get the most from the Java Concurrency API components ? Separate the thread management from the rest of the application with the Executor component ? Execute phased-based tasks in an efficient way with the Phaser components ? Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework ? Find out how to use parallel Streams and Reactive Streams ? Implement the “map and reduce” and “map and collect” programming models ? Control the concurrent data structures and synchronization mechanisms provided by the Java Concurrency API ? Implement efficient solutions for some actual problems such as data mining, machine learning, and more In Detail Concurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. Java 9 includes a comprehensive API with lots of ready-to-use components for easily implementing powerful concurrency applications, but with high flexibility so you can adapt these components to your needs. The book starts with a full de*ion of the design principles of concurrent applications and explains how to parallelize a sequential algorithm. You will then be introduced to Threads and Runnables, which are an integral part of Java 9's concurrency API. You will see how to use all the components of the Java concurrency API, from the basics to the most advanced techniques, and will implement them in powerful real-world concurrency applications. The book ends with a detailed de*ion of the tools and techniques you can use to test a concurrent Java application, along with a brief insight into other concurrency mechanisms in JVM. Style and approach This is a complete guide that implements real-world examples of algorithms related to machine learning, data mining, and natural language processing in client/server environments. All the examples are explained using a step-by-step approach.

Unleash the data processing and analytics capability of Apache Spark with the language of choice: Java About This Book ? Perform big data processing with Spark—without having to learn Scala! ? Use the Spark Java API to implement efficient enterprise-grade applications for data processing and analytics ? Go beyond mainstream data processing by adding querying capability, Machine Learning, and graph processing using Spark Who This Book Is For If you are a Java developer interested in learning to use the popular Apache Spark framework, this book is the resource you need to get started. Apache Spark developers who are looking to build enterprise-grade applications in Java will also find this book very useful. What You Will Learn ? Process data using different file formats such as XML, JSON, CSV, and plain and delimited text, using the Spark core Library. ? Perform analytics on data from various data sources such as Kafka, and Flume using Spark Streaming Library ? Learn SQL schema creation and the analysis of structured data using various SQL functions including Windowing functions in the Spark SQL Library ? Explore Spark Mlib APIs while implementing Machine Learning techniques to solve real-world problems ? Get to know Spark GraphX so you understand various graph-based analytics that can be performed with Spark In Detail Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone. The book starts with an introduction to the Apache Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when consuming Apache Spark's APIs. You will explore RDD and its associated common Action and Transformation Java APIs, set up a production-like clustered environment, and work with Spark SQL. Moving on, you will perform near-real-time processing with Spark streaming, Machine Learning analytics with Spark MLlib, and graph processing with GraphX, all using various Java packages. By the end of the book, you will have a solid foundation in implementing components in the Spark framework in Java to build fast, real-time applications. Style and approach This practical guide teaches readers the fundamentals of the Apache Spark framework and how to implement components using the Java language. It is a unique blend of theory and practical examples, and is written in a way that will gradually build your knowledge of Apache Spark.

Over 60 high-quality recipes covering debugging, security, performance, microservices, web frameworks, databases, deployment and more; rewritten for Node 4, 6, and 8. About This Book ? Security between Node.js and browser applications explained and applied in depth ? Cutting edge techniques and tools for measuring and improving performance ? Contemporary techniques to create developer-ergonomic, readily-scalable production systems Who This Book Is For If you have good knowledge of JavaScript and want to build fast, efficient, scalable client-server solutions, then this book is for you. Some experience with Node.js is assumed to get the most out of this book. If working from a beginner level Node Cookbook 2nd Edition is recommended as a primer for Node Cookbook 3rd Edition. What You Will Learn ? Rapidly become proficient at debugging Node.js programs ? Write and publish your own Node.js modules ? Become deeply acquainted with Node.js core API’s ? Use web frameworks such as Express, Hapi and Koa for accelerated web application development ? Apply Node.js streams for low-footprint infinite-capacity data processing ? Fast-track performance knowledge and optimization abilities ? Compare and contrast various persistence strategies, including database integrations with MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB ? Grasp and apply critically essential security concepts ? Understand how to use Node with best-of-breed deployment technologies: Docker, Kubernetes and AWS In Detail The principles of asynchronous event-driven programming are perfect for today's web, where efficient real-time applications and scalability are at the forefront. Server-side JavaScript has been here since the 90s but Node got it right. This edition is a complete rewrite of the original, and is targeted against Node 4, 6, and 8. It shows you how to build fast, efficient, and scalable client-server solutions using the latest versions of Node. Beginning with adopting debugging tips and tricks of the trade and learning how to write your own modules, then covering the fundamentals of streams in Node.js, you will go on to discover I/O control, implementation of various web protocols, you’ll work up to integrating with cross-section of databases such as MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB and building web application with Express, Hapi and Koa. You will then learn about security essentials in Node.js and the advanced optimization tools and techniques By the end of the book you should have acquired a level of proficiency that allows you to confidently build a full production-ready and scalable Node.js system. Style and approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient server side applications using the latest features and capabilities in Node 8 whilst also supporting usage with Node 4 and 6.

Viktor Farcic's latest book, The DevOps 2.1 Toolkit: Docker Swarm, shows you how to successfully integrate Docker Swarm into your DevOps toolset. About This Book ? Expand your DevOps Toolkit with the DevOps thought leader, Viktor Farcic ? Build, test, deploy, and monitor services inside Docker Swarm clusters ? Translate your understanding to different hosting providers like AWS, Azure, and DigitalOcean ? Go beyond simple deployment to explore how to create a continuous deployment process ? Extend the deep understanding you gained from Viktor's DevOps 2.0 Toolkit book Who This Book Is For This book is for professionals interested in the full microservices life cycle combined with continuous deployment and containers. Target audience could be architects who want to know how to design their systems around microservices. It could be DevOps wanting to know how to apply modern configuration management practices and continuously deploy applications packed in containers. It is for developers who would like to take the process back into their hands as well as for managers who would like to gain a better understanding of the process used to deliver software from the beginning to the end. This book is for everyone wanting to know more about the software development life cycle starting from requirements and design, through the development and testing all the way until deployment and post-deployment phases. We'll create the processes taking into account the best practices developed by and for some of the biggest companies. What You Will Learn ? Learn all aspects of Docker Swarm from building, testing, deploying, and monitoring services inside Docker Swarm clusters, available since Docker 1.12. ? Master the deeper logic of DevOps with Viktor, so that you can successfully apply that logic across any specific set of tools you’re working with. ? Translate a deep understanding to different hosting providers like AWS, Azure, DigitalOcean, among others. ? You’ll go beyond simple deployment: you will explore with Viktor how to create a continuous deployment process. Accomplish zero-downtime deployments, and what to do in case of a failover. ? Know how to run services at scale, how to monitor the systems, and how to make it heal itself. In Detail Viktor Farcic's latest book, The DevOps 2.1 Toolkit: Docker Swarm, takes you deeper into one of the major subjects of his international best seller, The DevOps 2.0 Toolkit, and shows you how to successfully integrate Docker Swarm into your DevOps toolset. Viktor shares with you his expert knowledge in all aspects of building, testing, deploying, and monitoring services inside Docker Swarm clusters. You'll go through all the tools required for running a cluster. You'll travel through the whole process with clusters running locally on a laptop. Once you're confident with that outcome, Viktor shows you how to translate your experience to different hosting providers like AWS, Azure, and DigitalOcean. Viktor has updated his DevOps 2.0 framework in this book to use the latest and greatest features and techniques introduced in Docker. We'll go through many practices and even more tools. While there will be a lot of theory, this is a hands-on book. You won't be able to complete it by reading it on the metro on your way to work. You'll have to read this book while in front of the computer and get your hands dirty. Style and approach We'll go through many practices and even more tools. While there will be a lot of theory, this is a hands-on book. You'll have to read this book while in front of the computer and get your hands dirty. The goal is not to master one particular set of tools, but to learn the logic behind them so that you can apply it to your job in various contexts.

Master the art of container management utilizing the power of Kubernetes. About This Book ? This practical guide demystifies Kubernetes and ensures that your clusters are always available, scalable, and up to date ? Discover new features such as autoscaling, rolling updates, resource quotas, and cluster size ? Master the skills of designing and deploying large clusters on various cloud platforms Who This Book Is For The book is for system administrators and developers who have intermediate level of knowledge with Kubernetes and are now waiting to master its advanced features. You should also have basic networking knowledge. This advanced-level book provides a pathway to master Kubernetes. What You Will Learn ? Architect a robust Kubernetes cluster for long-time operation ? Discover the advantages of running Kubernetes on GCE, AWS, Azure, and bare metal ? See the identity model of Kubernetes and options for cluster federation ? Monitor and troubleshoot Kubernetes clusters and run a highly available Kubernetes ? Create and configure custom Kubernetes resources and use third-party resources in your automation workflows ? Discover the art of running complex stateful applications in your container environment ? Deliver applications as standard packages In Detail Kubernetes is an open source system to automate the deployment, scaling, and management of containerized applications. If you are running more than just a few containers or want automated management of your containers, you need Kubernetes. This book mainly focuses on the advanced management of Kubernetes clusters. It covers problems that arise when you start using container orchestration in production. We start by giving you an overview of the guiding principles in Kubernetes design and show you the best practises in the fields of security, high availability, and cluster federation. You will discover how to run complex stateful microservices on Kubernetes including advanced features as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage back ends. Using real-world use cases, we explain the options for network configuration and provides guidelines on how to set up, operate, and troubleshoot various Kubernetes networking plugins. Finally, we cover custom resource development and utilization in automation and maintenance workflows. By the end of this book, you’ll know everything you need to know to go from intermediate to advanced level. Style and approach Delving into the design of the Kubernetes platform, the reader will be exposed to the advanced features and best practices of Kubernetes. This book will be an advanced level book which will provide a pathway to master Kubernetes

Learn how to develop web applications that deploy cross-platform and are optimized for high performance using ASP.NET Core 2 About This Book ? Master high-level web app performance improvement techniques using ASP.NET Core 2.0 ? Find the right balance between premature optimization and inefficient code ? Design workflows that run asynchronously and are resilient to transient performance issues Who This Book Is For This book is aimed for readers who can build a web application and have some experience with ASP.NET or some other web application framework (such as Ruby on Rails or Django). They can be people who are happy learning details independently but who struggle to discover the topics that they should be researching. The reader should be interested in improving the performance of their web app and in learning about ASP.NET Core and modern C#. What You Will Learn ? Understand ASP.NET Core 2 and how it differs from its predecessor ? Address performance issues at the early stages of development ? Set up development environments on Windows, Mac, and Linux ? Measure, profile and find the most significant problems ? Identify the differences between development workstations and production infrastructures, and how these can exacerbate problems ? Boost the performance of your application but with an eye to how it affects complexity and maintenance ? Explore a few cutting-edge techniques such as advanced hashing and custom transports In Detail The ASP.NET Core 2 framework is used to develop high-performance and cross-platform web applications. It is built on .NET Core 2 and includes significantly more framework APIs than version 1. This book addresses high-level performance improvement techniques. It starts by showing you how to locate and measure problems and then shows you how to solve some of the most common ones. Next, it shows you how to get started with ASP.NET Core 2 on Windows, Mac, Linux, and with Docker containers. The book illustrates what problems can occur as latency increases when deploying to a cloud infrastructure. It also shows you how to optimize C# code and choose the best data structures for the job. It covers new features in C# 6 and 7, along with parallel programming and distributed architectures. By the end of this book, you will be fixing latency issues and optimizing performance problems, but you will also know how this affects the complexity and maintenance of your application. Finally, we will explore a few highly advanced techniques for further optimization. Style and approach A step-by-step practical guide filled with real-world use cases and examples

Learn to implement DevOps using Docker & Kubernetes. About This Book ? Learning DevOps, container, and Kubernetes within one book. ? Leverage Kubernetes as a platform to deploy, scale, and run containers efficiently. ? A practical guide towards container management and orchestration Who This Book Is For This book is targeted for anyone, who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you’re advanced readers, you can also get a deeper understanding of all the tools and technique described in the book. What You Will Learn ? Learn fundamental and advanced DevOps skills and tools ? Get a comprehensive understanding for container ? Learn how to move your application to container world ? Learn how to manipulate your application by Kubernetes ? Learn how to work with Kubernetes in popular public cloud ? Improve time to market with Kubernetes and Continuous Delivery ? Learn how to monitor, log, and troubleshoot your application with Kubernetes In Detail Containerization is said to be the best way to implement DevOps. Google developed Kubernetes, which orchestrates containers efficiently and is considered the frontrunner in container orchestration. Kubernetes is an orchestrator that creates and manages your containers on clusters of servers. This book will guide you from simply deploying a container to administrate a Kubernetes cluster, and then you will learn how to do monitoring, logging, and continuous deployment in DevOps. The initial stages of the book will introduce the fundamental DevOps and the concept of containers. It will move on to how to containerize applications and deploy them into. The book will then introduce networks in Kubernetes. We then move on to advanced DevOps skills such as monitoring, logging, and continuous deployment in Kubernetes. It will proceed to introduce permission control for Kubernetes resources via attribute-based access control and role-based access control. The final stage of the book will cover deploying and managing your container clusters on the popular public cloud Amazon Web Services and Google Cloud Platform. At the end of the book, other orchestration frameworks, such as Docker Swarm mode, Amazon ECS, and Apache Mesos will be discussed. Style and approach Readers will be taken through fundamental DevOps skills and Kubernetes concept and administration with detailed examples. It introduces comprehensive DevOps topics, including microservices, automation tools, containers, monitoring, logging, continuous delivery, and popular public cloud environments. At each step readers will learn how to leverage Kubernetes in their everyday lives and transform their original delivery pipeline for fast and efficient delivery.