Learn everything you need to build highly scalable, robust web applications using Angular release 4 About This Book ? Apply best practices and design patterns to achieve higher scalability in your Angular applications ? Understand the latest features of Angular and create your own components ? Get acquainted with powerful, advanced techniques in Angular to build professional web applications Who This Book Is For This book is for JavaScript developers with some prior exposure to Angular, at least through basic examples. We assume that you’ve got working knowledge of HTML, CSS, and JavaScript. What You Will Learn ? Implement asynchronous programming using Angular ? Beautify your application with the UI components built to the material design specification ? Secure your web application from unauthorized users ? Create complex forms, taking full advantage of 2-way data binding ? Test your Angular applications using the Jasmine and Protractor frameworks for better efficiency ? Learn how to integrate Angular with Bootstrap to create compelling web applications ? Use Angular built-in classes to apply animation in your app In Detail Got some experience of Angular under your belt? Want to learn everything about using advanced features for developing websites? This book is everything you need for the deep understanding of Angular that will set you apart from the developer crowd. Angular has introduced a new way to build applications. Creating complex and rich web applications, with a lighter resource footprint, has never been easier or faster. Angular is now at release 4, with significant changes through previous versions. This book has been written and tested for Angular release 4. Angular is a mature technology, and you'll likely have applications built with earlier versions. This book starts by showing you best practices and approaches to migrating your existing Angular applications so that you can be immediately up-to-date. You will take an in-depth look at components and see how to control the user journey in your applications by implementing routing and navigation. You will learn how to work with asynchronous programming by using Observables. To easily build applications that look great, you will learn all about template syntax and how to beautify applications with Material Design. Mastering forms and data binding will further speed up your application development time. Learning about managing services and animations will help you to progressively enhance your applications. Next you’ll use native directives to integrate Bootstrap with Angular. You will see the best ways to test your application with the leading options such as Jasmine and Protractor. At the end of the book, you’ll learn how to apply design patterns in Angular, and see the benefits they will bring to your development. Style and approach This book provides comprehensive coverage of all aspects of development with Angular. You will learn about all the most powerful Angular concepts, with examples and best practices. This book is everything you need for the deep understanding of Angular that will set you apart from the developer crowd.

Develop deep neural networks in Theano with practical code examples for image classification, machine translation, reinforcement agents, or generative models. About This Book ? Learn Theano basics and evaluate your mathematical expressions faster and in an efficient manner ? Learn the design patterns of deep neural architectures to build efficient and powerful networks on your datasets ? Apply your knowledge to concrete fields such as image classification, object detection, chatbots, machine translation, reinforcement agents, or generative models. Who This Book Is For This book is indented to provide a full overview of deep learning. From the beginner in deep learning and artificial intelligence, to the data scientist who wants to become familiar with Theano and its supporting libraries, or have an extended understanding of deep neural nets. Some basic skills in Python programming and computer science will help, as well as skills in elementary algebra and calculus. What You Will Learn ? Get familiar with Theano and deep learning ? Provide examples in supervised, unsupervised, generative, or reinforcement learning. ? Discover the main principles for designing efficient deep learning nets: convolutions, residual connections, and recurrent connections. ? Use Theano on real-world computer vision datasets, such as for digit classification and image classification. ? Extend the use of Theano to natural language processing tasks, for chatbots or machine translation ? Cover artificial intelligence-driven strategies to enable a robot to solve games or learn from an environment ? Generate synthetic data that looks real with generative modeling ? Become familiar with Lasagne and Keras, two frameworks built on top of Theano In Detail This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models easy on CPU or GPU. The book provides some practical code examples that help the beginner understand how easy it is to build complex neural networks, while more experimented data scientists will appreciate the reach of the book, addressing supervised and unsupervised learning, generative models, reinforcement learning in the fields of image recognition, natural language processing, or game strategy. The book also discusses image recognition tasks that range from simple digit recognition, image classification, object localization, image segmentation, to image captioning. Natural language processing examples include text generation, chatbots, machine translation, and question answering. The last example deals with generating random data that looks real and solving games such as in the Open-AI gym. At the end, this book sums up the best -performing nets for each task. While early research results were based on deep stacks of neural layers, in particular, convolutional layers, the book presents the principles that improved the efficiency of these architectures, in order to help the reader build new custom nets. Style and approach It is an easy-to-follow example book that teaches you how to perform fast, efficient computations in Python. Starting with the very basics-NumPy, installing Theano, this book will take you to the smooth journey of implementing Theano for advanced computations for machine learning and deep learning.

This unique book provides you with a wealth of tips, tricks, best practices, and answers to the day-to-day questions that programmers face in their careers. It is split into three parts: Coder Skills, Freelancer Skills, and Career Skills, providing the knowledge you need to get ahead in programming. About This Book ? Over 50 essays with practical advice on improving your programming career ? Practical focus gives solutions to common problems, and methods to become a better coder ? Includes advice for existing programmers and those wanting to begin a career in programming Who This Book Is For This book is useful for programmers of any ability or discipline. It has advice for those thinking about beginning a career in programming, those already working as a fully employed programmer, and for those working as freelance developers. What You Will Learn ? Improve your soft skills to become a better and happier coder ? Learn to be a better developer ? Grow your freelance development business ? Improve your development career ? Learn the best approaches to breaking down complex topics ? Have the confidence to charge what you're worth as a freelancer ? Succeed in developer job interviews In Detail This is an all-purpose toolkit for your programming career. It has been built by Jordan Hudgens over a lifetime of coding and teaching coding. It helps you identify the key questions and stumbling blocks that programmers encounter, and gives you the answers to them! It is a comprehensive guide containing more than 50 insights that you can use to improve your work, and to give advice in your career. The book is split up into three topic areas: Coder Skills, Freelancer Skills, and Career Skills, each containing a wealth of practical advice. Coder Skills contains advice for people starting out, or those who are already working in a programming role but want to improve their skills. It includes such subjects as: how to study and understand complex topics, and getting past skill plateaus when learning new languages. Freelancer Skills contains advice for developers working as freelancers or with freelancers. It includes such subjects as: knowing when to fire a client, and tips for taking over legacy applications. Career Skills contains advice for building a successful career as a developer. It includes such subjects as: how to improve your programming techniques, and interview guides and developer salary negotiation strategies. Style and approach This unique book provides over 50 insightful essays full of practical advice for improving your programming career. The book is split into three broad sections covering different aspects of a developer's career. Each essay is self-contained and can be read individually, or in chunks.

Make sense of your data and predict the unpredictable About This Book ? A unique book that centers around develop six key practical skills needed to develop and implement predictive analytics ? Apply the principles and techniques of predictive analytics to effectively interpret big data ? Solve real-world analytical problems with the help of practical case studies and real-world scenarios taken from the world of healthcare, marketing, and other business domains Who This Book Is For This book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues. Basic familiarity with a programming language of R is expected. What You Will Learn ? Master the core predictive analytics algorithm which are used today in business ? Learn to implement the six steps for a successful analytics project ? Classify the right algorithm for your requirements ? Use and apply predictive analytics to research problems in healthcare ? Implement predictive analytics to retain and acquire your customers ? Use text mining to understand unstructured data ? Develop models on your own PC or in Spark/Hadoop environments ? Implement predictive analytics products for customers In Detail This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a de*ion of the best practices for organizing your projects. On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model. We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data. Style and Approach This book takes a practical hands-on approach wherein the algorithms will be explained with the help of real-world use cases. It is written in a well-researched academic style which is a great mix of theoretical and practical information. Code examples are supplied for both theoretical concepts as well as for the case studies. Key references and summaries will be provided at the end of each chapter so that you can explore those topics on their own.

Gain a thorough understanding of operating in a Python development environment, and some of the most important advanced topics with Daniel Arbuckle. This dynamic, concise book is full of real-world solutions for Python 3.6 problems, and advanced-level concepts such as reactive programming, microservices, ctypes and Cython. About This Book ? Covers the latest and advanced concepts of Python such as parallel processing with Python 3.6 ? Explore the Python language from its basic installation and setup to concepts such as reactive programming and microservices ? Get introduced to the mechanism for rewriting code in a compiled language along with ctypes and Cython tools Who This Book Is For If you are a programmer and are familiar with the basics of Python, and you want to broaden your knowledge base to develop projects better and faster, this book is for you. Even if you are not familiar with Python, Daniel Arbuckle's Mastering Python starts with the basics and takes you on a journey to become an expert in the technology. What You Will Learn ? Get to grips with the basics of operating in a Python development environment ? Build Python packages to efficiently create reusable code ? Become proficient at creating tools and utility programs in Python ? Use the Git version control system to protect your development environment from unwanted changes ? Harness the power of Python to automate other software ? Distribute computational tasks across multiple processors ? Handle high I/O loads with asynchronous I/O to get a smoother performance ? Take advantage of Python's metaprogramming and programmable syntax features ? Get acquainted with the concepts behind reactive programming and RxPy In Detail Daniel Arbuckle's Mastering Python covers the basics of operating in a Python development environment, before moving on to more advanced topics. Daniel presents you with real-world solutions to Python 3.6 and advanced-level concepts, such as reactive programming, microservices, ctypes, and Cython tools. You don't need to be familiar with the Python language to use this book, as Daniel starts with a Python primer. Throughout, Daniel highlights the major aspects of managing your Python development environment, shows you how to handle parallel computation, and helps you to master asynchronous I/O with Python 3.6 to improve performance. Finally, Daniel will teach you the secrets of metaprogramming and unit testing in Python, helping you acquire the perfect skillset to be a Python expert. Daniel will get you up to speed on everything from basic programming practices to high-end tools and techniques, things that will help set you apart as a successful Python programmer. Style and Approach Daniel Arbuckle's Mastering Python covers basic to advanced-level concepts in computer science. If you are a beginner, then Daniel will help you get started. If you are experienced, he will expand your knowledge base.

Store, search, and analyze your data with ease using Elasticsearch 5.x About This Book ? Get to grips with the basics of Elasticsearch concepts and its APIs, and use them to create efficient applications ? Create large-scale Elasticsearch clusters and perform analytics using aggregation ? This comprehensive guide will get you up and running with Elasticsearch 5.x in no time Who This Book Is For If you want to build efficient search and analytics applications using Elasticsearch, this book is for you. It will also benefit developers who have worked with Lucene or Solr before and now want to work with Elasticsearch. No previous knowledge of Elasticsearch is expected. What You Will Learn ? See how to set up and configure Elasticsearch and Kibana ? Know how to ingest structured and unstructured data using Elasticsearch ? Understand how a search engine works and the concepts of relevance and scoring ? Find out how to query Elasticsearch with a high degree of performance and scalability ? Improve the user experience by using autocomplete, geolocation queries, and much more ? See how to slice and dice your data using Elasticsearch aggregations. ? Grasp how to use Kibana to explore and visualize your data ? Know how to host on Elastic Cloud and how to use the latest X-Pack features such as Graph and Alerting In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently. You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments. Style and approach This comprehensive guide will get you started with Elasticsearch 5.x, so you build a solid understanding of the basics. Every topic is explained in depth and is supplemented with practical examples to enhance your understanding.

Click your way to automating various business processes using Salesforce Visual Workflow About This Book ? Develop an application using Point and Click with the help of Flow ? Get to grips with various ways to launch a Flow ? Capture data from an external user without using the Visualforce page ? Save user input into the database, and learn how to query and manipulate the data ? Discover various ways to debug and deploy Flow and Process Builder ? Understand the concepts of Subflow and Login Flow ? Handle complex business processes using Process builder and keep them clean ? Use existing or new Flows to work with Salesforce Lightning Experience. Who This Book Is For This book is intended for those who want to use Flows to automate their business requirements by clicking, not coding. No previous experience in computer coding or programming is required. What You Will Learn ? Develop an application using point and click with the help of Flow ? Get to grips with various ways to launch a Flow ? Capture data from an external user without using the Visualforce page ? Save user input into the database, and learn how to query and manipulate the data ? Discover various ways to debug and deploy Flow and Process Builder ? Understand the concepts of Subflow and Login Flow ? Handle complex business processes using Process builder and keep them clean ? Use existing or new Flows to work with Salesforce Lightning Experience. In Detail Salesforce Management System is an information system used in CRM to automate the business processes like sales and marketing. To implement this, Force.com developed a powerful tool called Visual Workflow to automate business processes by creating applications also called Flows. Learning Salesforce Visual Workflow, Second Edition is a practical guide on Flows that will enable you to develop custom applications in Salesforce with minimized code usage. The book starts with an introduction to Visual Workflows that teaches all the building blocks of creating Flows and use it efficiently. You will learn how to easily automate business processes and tackle complex business scenarios using Flows. The book explains the working of the Process Builder so you can create reusable processes. The book also covers how you can integrate existing or newly created Flows with the Salesforce Lightening Experience. By the end of the book, you will get a clear understanding on how to use Flows and Process Builder in your organization to optimize code usage. Style and approach Step by step approch to use Process Builder to solve complex business requirements with the help of Flow

The quick start guide for an advanced enterprise PowerShell framework About This Book ? Introduces industry-proven techniques that improve * efficiency and reliability ? Example-rich guide based on real-world scenarios ? Facilitates building a * that can fully scan a Windows server and identify components Who This Book Is For This book is for IT professionals and Windows administrators who would like to gain intensive, hands-on knowledge and skills on PowerShell without spending hours and hours in learning. If you have been struggling to find the time to gain proficiency and confidence with PowerShell and everyday *ing tasks What You Will Learn ? Create an advanced PowerShell *ing template that provides repeatable code to jumpstart all of your *ing projects ? Learn how to securely encrypt and store usernames, passwords, and other sensitive data in PowerShell *s and answer files ? Understand how to optimize the performance of *s to help process large datasets quickly and avoid time-consuming mistakes ? Develop a * to scan for non-standard Windows Server configurations and identify service accounts used on Windows Servers ? Gather a large list of data from a Windows server without locally or remotely logging in interactively In Detail Enterprise PowerShell Scripting Bootcamp explains how to create your own repeatable PowerShell *ing framework. This framework contains * logging methodologies, answer file interactions, and string encryption and decryption strategies. This book focuses on evaluating individual components to identify the system’s function, role, and unique characteristics. To do this, you will leverage built-in CMDlets and Windows Management Instrumentation (WMI) to explore Windows services, Windows processes, Windows features, scheduled tasks, and disk statistics. You will also create custom functions to perform a deep search for specific strings in files and evaluate installed software through executable properties. We will then discuss different *ing techniques to improve the efficiency of *s. By leveraging several small changes to your code, you can increase the execution performance by over 130%. By the end of this book, you will be able to tie all of the concepts together in a PowerShell-based Windows server scanning *. This discovery * will be able to scan a Windows server to identify a multitude of components. Style and approach This book is all about fast and intensive learning. This means, we don’t waste time in helping readers get started. The new content is about leveraging highly-effective examples to build new things, help solving problems in newer and unseen ways, and providing an enterprise-ready platform to create PowerShell Scripts.

Over 90 recipes to maximize automated solutions and policy-drive application profiles using Cisco ACI About This Book ? Confidently provision your virtual and physical infrastructure for application deployment ? Integrate Cisco ACI with hypervisors and other third party devices ? Packed with powerful recipes to automate your IT operations Who This Book Is For If you are a network administrator, system administrator, or engineer and are aware of the basics of Cisco ACI but want to start using it to automate your tasks, then this book is for you What You Will Learn ? Master the Cisco ACI architecture ? Discover the ACI fabric with easy-to-follow steps ? Set up quality of service within ACI ? Configure external networks with Cisco ACI ? Integrate with VMware and track VMware virtual machines ? Configure apply and verify access policies ? Extend or migrate a VMware virtual-machine LAN inside the ACI fabric ? Monitor ACI with third party tools and troubleshoot issues In Detail Cisco Application Centric Infrastructure (ACI) is a tough architecture that automates IT tasks and accelerates data-center application deployments. This book focuses on practical recipes to help you quickly build, manage, and customize hybrid environment for your organization using Cisco ACI. You will begin by understanding the Cisco ACI architecture and its major components. You will then configure Cisco ACI policies and tenants. Next you will connect to hypervisors and other third-party devices. Moving on, you will configure routing to external networks and within ACI tenants and also learn to secure ACI through RBAC. Furthermore, you will understand how to set up quality of service and network programming with REST, XML, Python and so on. Finally you will learn to monitor and troubleshoot ACI in the event of any issues that arise. By the end of the book, you will gain have mastered automating your IT tasks and accelerating the deployment of your applications. Style and approach A set of exciting recipes to automate your IT operations related to datacenters, the Cloud, and networking tasks

Master over 80 object-oriented recipes to create amazing GUIs in Python and revolutionize your applications today About This Book ? Use object-oriented programming to develop amazing GUIs in Python ? Create a working GUI project as a central resource for developing your Python GUIs ? Easy-to-follow recipes to help you develop code using the latest released version of Python Who This Book Is For This book is for intermediate Python programmers who wish to enhance their Python skills by writing powerful GUIs in Python. As Python is such a great and easy to learn language, this book is also ideal for any developer with experience of other languages and enthusiasm to expand their horizon. What You Will Learn ? Create the GUI Form and add widgets ? Arrange the widgets using layout managers ? Use object-oriented programming to create GUIs ? Create Matplotlib charts ? Use threads and talking to networks ? Talk to a MySQL database via the GUI ? Perform unit-testing and internationalizing the GUI ? Extend the GUI with third-party graphical libraries ? Get to know the best practices to create GUIs In Detail Python is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a *ing language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Python GUI Programming Cookbook follows a task-based approach to help you create beautiful and very effective GUIs with the least amount of code necessary. This book will guide you through the very basics of creating a fully functional GUI in Python with only a few lines of code. Each and every recipe adds more widgets to the GUIs we are creating. While the cookbook recipes all stand on their own, there is a common theme running through all of them. As our GUIs keep expanding, using more and more widgets, we start to talk to networks, databases, and graphical libraries that greatly enhance our GUI’s functionality. This book is what you need to expand your knowledge on the subject of GUIs, and make sure you’re not missing out in the long run. Style and approach This programming cookbook consists of standalone recipes, and this approach makes it unique.. While each recipe explains a certain concept, throughout the book you’ll build a more and more advanced GUI, recipe after recipe. In some of the advanced topics, we simply create a new GUI in order to explore these topics in depth.

Implement classic and functional data structures and algorithms using Python About This Book ? A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures. ? Get a better understanding of advanced Python concepts such as big-o notation, dynamic programming, and functional data structures. ? Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Who This Book Is For The book will appeal to Python developers. A basic knowledge of Python is expected. What You Will Learn ? Gain a solid understanding of Python data structures. ? Build sophisticated data applications. ? Understand the common programming patterns and algorithms used in Python data science. ? Write efficient robust code. In Detail Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications. Style and approach The easy-to-read book with its fast-paced nature will improve the productivity of Python programmers and improve the performance of Python applications.

Take tiny steps to enter the big world of data science through this interesting guide About This Book ? Learn the fundamentals of machine learning and build your own intelligent applications ? Master the art of building your own machine learning systems with this example-based practical guide ? Work with important classification and regression algorithms and other machine learning techniques Who This Book Is For This book is for anyone interested in entering the data science stream with machine learning. Basic familiarity with Python is assumed. What You Will Learn ? Exploit the power of Python to handle data extraction, manipulation, and exploration techniques ? Use Python to visualize data spread across multiple dimensions and extract useful features ? Dive deep into the world of analytics to predict situations correctly ? Implement machine learning classification and regression algorithms from scratch in Python ? Be amazed to see the algorithms in action ? Evaluate the performance of a machine learning model and optimize it ? Solve interesting real-world problems using machine learning and Python as the journey unfolds In Detail Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms – they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal. Style and approach This book is an enticing journey that starts from the very basics and gradually picks up pace as the story unfolds. Each concept is first succinctly defined in the larger context of things, followed by a detailed explanation of their application. Every concept is explained with the help of a project that solves a real-world problem, and involves hands-on work—giving you a deep insight into the world of machine learning. With simple yet rich language—Python—you will understand and be able to implement the examples with ease.

Get command of your organizational Big Data using the power of data science and analytics About This Book ? A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions ? Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses ? Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Who This Book Is For The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience. What You Will Learn ? Get a 360-degree view into the world of Big Data, data science and machine learning ? Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives ? Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R ? Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions ? Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications ? Understand corporate strategies for successful Big Data and data science projects ? Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies In Detail Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. Style and approach This book equips you with a knowledge of various NoSQL tools, R, Python programming, cloud platforms, and techniques so you can use them to store, analyze, and deliver meaningful insights from your data.

Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book ? Learn how to apply complex visual effects to images with OpenCV 3.x and Python ? Extract features from an image and use them to develop advanced applications ? Build algorithms to help you understand image content and perform visual searches ? Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn ? Detect shapes and edges from images and videos ? How to apply filters on images and videos ? Use different techniques to manipulate and improve images ? Extract and manipulate particular parts of images and videos ? Track objects or colors from videos ? Recognize specific object or faces from images and videos ? How to create Augmented Reality applications ? Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. Style and approach The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.

Transform yourself into a Kubernetes specialist in serverless applications. About This Book ? Get hands-on experience in installing, configuring, and using services such as Kubeless, Funktion, OpenWhisk, and Fission ? Learn how to launch Kubernetes both locally and in public clouds ? Explore the differences between using services such as AWS Lambda and Azure Functions and running your own Who This Book Is For If you are a DevOps engineer, cloud architect, or a stakeholder keen to learn about serverless functions in Kubernetes environments, then this book is for you. What You Will Learn ? Get a detailed analysis of serverless/Functions as a Service ? Get hands-on with installing and running tasks in Kubernetes using Minikube ? Install Kubeless locally and launch your first function. ? Launch Kubernetes in the cloud and move your applications between your local machine and your cloud cluster ? Deploy applications on Kubernetes using Apache OpenWhisk ? Explore topics such as Funktion and Fission installation on the cloud followed by launching applications ? Monitor a serverless function and master security best practices and Kubernetes use cases In Detail Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. It has been adopted by companies such as Google, its original developers, and Microsoft as an integral part of their public cloud platforms, so that you can develop for Kubernetes and not worry about being locked into a single vendor. This book will initially start by introducing serverless functions. Then you will configure tools such as Minikube to run Kubernetes. Once you are up-and-running, you will install and configure Kubeless, your first step towards running Function as a Service (FaaS) on Kubernetes. Then you will gradually move towards running Fission, a framework used for managing serverless functions on Kubernetes environments. Towards the end of the book, you will also work with Kubernetes functions on public and private clouds. By the end of this book, we will have mastered using Function as a Service on Kubernetes environments. Style and approach A clear, concise, and straightforward book that will empower you work with clusters and run serverless functions effectively.

Deploy and manage VMware vSphere 6.5 components with ease. About This Book ? Simplified and to-the-point theory and practical recipes to deploy and manage vSphere 6.5 ? Discover the best ways to deploy stateless and stateful ESXi hosts and upgrade them ? Storage and network resource management ? Certificate management using VMCA ? Monitor the performance of a vSphere environment. Who This Book Is For If you are a system administrator, support professional, or anyone interested in learning how to install, configure, and manage a vSphere environment, then this book is for you. This task-oriented reference guide will also benefit consultants or infrastructure architects who design and deploy vSphere 6.5 environments. What You Will Learn ? Upgrade your existing vSphere environment or perform a fresh deployment. ? Automate the deployment and management of large sets of ESXi hosts in your vSphere Environment ? Configure and manage FC, iSCSI, and NAS storage, and get more control over how storage resources are allocated and managed ? Configure vSphere networking by deploying host-wide and data center-wide switches in your vSphere environment ? Configure high availability on a host cluster and learn how to enable the fair distribution and utilization of compute resources ? Patch and upgrade the vSphere environment ? Handle certificate request generation and renew component certificates ? Monitor performance of a vSphere environment In Detail VMware vSphere is a complete and robust virtualization product suite that helps transform data centers into simplified on-premises cloud infrastructures, providing for the automation and orchestration of workload deployment and life cycle management of the infrastructure. This book focuses on the latest release of VMware vSphere and follows a recipe-based approach, giving you hands-on instructions required to deploy and manage a vSphere environment. The book starts with the procedures involved in upgrading your existing vSphere infrastructure to vSphere 6.5, followed by deploying a new vSphere 6.5 environment. Then the book delves further into the procedures involved in managing storage and network access to the ESXi hosts and the virtual machines running on them. Moving on, the book covers high availability and fair distribution/utilization of clustered compute and storage resources. Finally, the book covers patching and upgrading the vSphere infrastructure using VUM, certificate management using VMCA, and finishes with a chapter covering the tools that can be used to monitor the performance of a vSphere infrastructure. Style and approach This book will quickly get you started with managing VMware components.

Take a deep dive into building data-driven test frameworks using Selenium WebDriver About This Book ? A comprehensive guide to designing data-driven test frameworks using the Selenium 3 WebDriver API, AppiumDriver API, Java-Bindings, and TestNG ? Learn how to use Selenium Page Object Design Patterns and D.R.Y. (Don’t Repeat Yourself) Approaches to software development in automated testing ? Discover the Selenium Grid Architecture and build your own grid for browser and mobile devices ? Use third party tools and services like ExtentReports for results processing, reporting, and SauceLabs for cloud-based test services Who This Book Is For This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications.This book is geared towards the quality assurance and development professionals responsible for designing and building enterprise-based testing frameworks.The user should have a working knowledge of the Java, TestNG, and Selenium technologies What You Will Learn ? Design the Selenium Driver Class for local, remote, and third party grid support ? Build Page Object Classes using the Selenium Page Object Model ? Develop Data-Driven Test Classes using the TestNG framework ? Encapsulate Data using the JSON Protocol ? Build a Selenium Grid for RemoteWebDriver Testing ? Construct Utility Classes for use in Synchronization, File I/O, Reporting and Test Listener Classes ? Run the sample framework and see the benefits of a live data-driven framework in real-time In Detail The Selenium WebDriver 3.x Technology is an open source API available to test both Browser and Mobile applications. It is completely platform independent in that tests built for one browser or mobile device, will also work on all other browsers and mobile devices. Selenium supports all major development languages which allow it to be tied directly into the technology used to develop the applications. This guide will provide a step-by-step approach to designing and building a data-driven test framework using Selenium WebDriver, Java, and TestNG. The book starts off by introducing users to the Selenium Page Object Design Patterns and D.R.Y Approaches to Software Development. In doing so, it covers designing and building a Selenium WebDriver framework that supports both Browser and Mobile Devices. It will lead the user through a journey of architecting their own framework with a scalable driver class, Java utility classes, JSON Data Provider, Data-Driven Test Classes, and support for third party tools and plugins. Users will learn how to design and build a Selenium Grid from scratch to allow the framework to scale and support different browsers, mobile devices, versions, and platforms, and how they can leverage third party grids in the Cloud like SauceLabs. Other topics covered include designing abstract base and sub-classes, inheritance, dual-driver support, parallel testing, testing multi-branded applications, best practices for using locators, and data encapsulation. Finally, you will be presented with a sample fully-functional framework to get them up and running with the Selenium WebDriver for browser testing. By the end of the book, you will be able to design your own automation testing framework and perform data-driven testing with Selenium WebDriver. Style and approach A comprehensive approach to designing data-driven test frameworks using the Selenium 3 WebDriver API, Java-Bindings, and TestNG Technologies

Explore the concepts and tools you need to discover the world of microservices with various design patterns About This Book ? Get to grips with the microservice architecture and build enterprise-ready microservice applications ? Learn design patterns and the best practices while building a microservice application ? Obtain hands-on techniques and tools to create high-performing microservices resilient to possible fails Who This Book Is For This book is for architects and senior developers who would like implement microservice design patterns in their enterprise application development. The book assumes some prior programming knowledge. What You Will Learn ? How to break monolithic application into microservices ? Implement caching strategies, CQRS and event sourcing, and circuit breaker patterns ? Incorporate different microservice design patterns, such as shared data, aggregator, proxy, and chained ? Utilize consolidate testing patterns such as integration, signature, and monkey tests ? Secure microservices with JWT, API gateway, and single sign on ? Deploy microservices with continuous integration or delivery, Blue-Green deployment In Detail Microservices are a hot trend in the development world right now. Many enterprises have adopted this approach to achieve agility and the continuous delivery of applications to gain a competitive advantage. This book will take you through different design patterns at different stages of the microservice application development along with their best practices. Microservice Patterns and Best Practices starts with the learning of microservices key concepts and showing how to make the right choices while designing microservices. You will then move onto internal microservices application patterns, such as caching strategy, asynchronism, CQRS and event sourcing, circuit breaker, and bulkheads. As you progress, you'll learn the design patterns of microservices. The book will guide you on where to use the perfect design pattern at the application development stage and how to break monolithic application into microservices. You will also be taken through the best practices and patterns involved while testing, securing, and deploying your microservice application. At the end of the book, you will easily be able to create interoperable microservices, which are testable and prepared for optimum performance. Style and approach Comprehensive guide that uses architectural patterns with the best choices involved in application development

Build effective regression models in R to extract valuable insights from real data About This Book ? Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values ? From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R ? A complete guide to building effective regression models in R and interpreting results from them to make valuable predictions Who This Book Is For This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful What You Will Learn ? Get started with the journey of data science using Simple linear regression ? Deal with interaction, collinearity and other problems using multiple linear regression ? Understand diagnostics and what to do if the assumptions fail with proper analysis ? Load your dataset, treat missing values, and plot relationships with exploratory data analysis ? Develop a perfect model keeping overfitting, under-fitting, and cross-validation into consideration ? Deal with classification problems by applying Logistic regression ? Explore other regression techniques – Decision trees, Bagging, and Boosting techniques ? Learn by getting it all in action with the help of a real world case study. In Detail Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples. By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Regression Analysis with R

Master the capabilities of PostgreSQL 10 to efficiently manage and maintain your database About This Book ? Your one-stop guide to mastering advanced concepts in PostgreSQL 10 with ease ? Master query optimization, replication, and high availability with PostgreSQL ? Extend the functionalities of your PostgreSQL instance to suit your organizational needs with minimal effort Who This Book Is For If you are a PostgreSQL data architect or an administrator and want to understand how to implement advanced functionalities and master complex administrative tasks with PostgreSQL 10, then this book is perfect for you. Prior experience of administrating a PostgreSQL database and a working knowledge of SQL are required to make the best use of this book. What You Will Learn ? Get to grips with the advanced features of PostgreSQL 10 and handle advanced SQL ? Make use of the indexing features in PostgreSQL and fine-tune the performance of your queries ? Work with stored procedures and manage backup and recovery ? Master replication and failover techniques ? Troubleshoot your PostgreSQL instance for solutions to common and not-so-common problems ? Learn how to migrate your database from MySQL and Oracle to PostgreSQL without any hassle In Detail PostgreSQL is an open source database used for handling large datasets (big data) and as a JSON document database. This book highlights the newly introduced features in PostgreSQL 10, and shows you how you can build better PostgreSQL applications, and administer your PostgreSQL database more efficiently. We begin by explaining advanced database design concepts in PostgreSQL 10, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery, high availability, and much more. You will understand common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL 10. Style and approach This mastering-level guide delves into the advanced functionalities of PostgreSQL 10

A practical guide designed to get you from basics to current state of art in computer vision systems. About This Book ? Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease ? Leverage the power of Python, Tensorflow, Keras, and OpenCV to perform image processing, object detection, feature detection and more ? With real-world datasets and fully functional code, this book is your one-stop guide to understanding Computer Vision Who This Book Is For This book is for machine learning practitioners and deep learning enthusiasts who want to understand and implement various tasks associated with Computer Vision and image processing in the most practical manner possible. Some programming experience would be beneficial while knowing Python would be an added bonus. What You Will Learn ? Learn the basics of image manipulation with OpenCV ? Implement and visualize image filters such as smoothing, dilation, histogram equalization, and more ? Set up various libraries and platforms, such as OpenCV, Keras, and Tensorflow, in order to start using computer vision, along with appropriate datasets for each chapter, such as MSCOCO, MOT, and Fashion-MNIST ? Understand image transformation and downsampling with practical implementations. ? Explore neural networks for computer vision and convolutional neural networks using Keras ? Understand working on deep-learning-based object detection such as Faster-R-CNN, SSD, and more ? Explore deep-learning-based object tracking in action ? Understand Visual SLAM techniques such as ORB-SLAM In Detail In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects. With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications. Style and approach Step-by-step guide filled with real-world, practical examples for understanding and applying various Computer Vision techniques