Use Wireshark 2 to overcome real-world network problems About This Book ? Delve into the core functionalities of the latest version of Wireshark ? Master network security skills with Wireshark 2 ? Efficiently find the root cause of network-related issues Who This Book Is For If you are a security professional or a network enthusiast and are interested in understanding the internal working of networks, and if you have some prior knowledge of using Wireshark, then this book is for you. What You Will Learn ? Understand what network and protocol analysis is and how it can help you ? Use Wireshark to capture packets in your network ? Filter captured traffic to only show what you need ? Explore useful statistic displays to make it easier to diagnose issues ? Customize Wireshark to your own specifications ? Analyze common network and network application protocols In Detail Wireshark, a combination of a Linux distro (Kali) and an open source security framework (Metasploit), is a popular and powerful tool. Wireshark is mainly used to analyze the bits and bytes that flow through a network. It efficiently deals with the second to the seventh layer of network protocols, and the analysis made is presented in a form that can be easily read by people. Mastering Wireshark 2 helps you gain expertise in securing your network. We start with installing and setting up Wireshark2.0, and then explore its interface in order to understand all of its functionalities. As you progress through the chapters, you will discover different ways to create, use, capture, and display filters. By halfway through the book, you will have mastered Wireshark features, analyzed different layers of the network protocol, and searched for anomalies. You’ll learn about plugins and APIs in depth. Finally, the book focuses on pocket analysis for security tasks, command-line utilities, and tools that manage trace files. By the end of the book, you'll have learned how to use Wireshark for network security analysis and configured it for troubleshooting purposes. Style and approach This step-by-step guide on Wireshark 2 starts with capturing and filtering traffic and follows with analysis and statistics, as well as all the new features of Wireshark 2.

Solve real-world data problems with R and machine learning Key Features * Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond * Harness the power of R to build flexible, effective, and transparent machine learning models * Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R. What you will learn * Discover the origins of machine learning and how exactly a computer learns by example * Prepare your data for machine learning work with the R programming language * Classify important outcomes using nearest neighbor and Bayesian methods * Predict future events using decision trees, rules, and support vector machines * Forecast numeric data and estimate financial values using regression methods * Model complex processes with artificial neural networks — the basis of deep learning * Avoid bias in machine learning models * Evaluate your models and improve their performance * Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow Who this book is for Data scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.

Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features * Design and create neural network architectures on different domains using Keras * Integrate neural network models in your applications using this highly practical guide * Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn * Understand the fundamental nature and workflow of predictive data modeling * Explore how different types of visual and linguistic signals are processed by neural networks * Dive into the mathematical and statistical ideas behind how networks learn from data * Design and implement various neural networks such as CNNs, LSTMs, and GANs * Use different architectures to tackle cognitive tasks and embed intelligence in systems * Learn how to generate synthetic data and use augmentation strategies to improve your models * Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.

Write efficient, reusable scripts to build custom characters, game environments, and control enemy AI Key Features * Build captivating multiplayer games using Unreal Engine and C++ * Incorporate existing C++ libraries into your game to add extra functionality such as hardware integration * Practical solutions for memory management, error handling, inputs, and collision for your game codebase Book Description Unreal Engine 4 (UE4) is a popular and award-winning game engine that powers some of the most popular games. A truly powerful tool for game development, there has never been a better time to use it for both commercial and independent projects. With more than 100 recipes, this book shows how to unleash the power of C++ while developing games with Unreal Engine. This book takes you on a journey to jumpstart your C++ and UE4 development skills. You will start off by setting up UE4 for C++ development and learn how to work with Visual Studio, a popular code editor. You will learn how to create C++ classes and structs the Unreal way. This will be followed by exploring memory management, smart pointers, and debugging your code. You will then learn how to make your own Actors and Components through code and how to handle input and collision events. You will also get exposure to many elements of game development including creating user interfaces, artificial intelligence, and writing code with networked play in mind. You will also learn how to add on to the Unreal Editor itself. With a range of task-oriented recipes, this book provides actionable information about writing code for games with UE4 using C++. By the end of the book, you will be empowered to become a top-notch developer with UE4 using C++ as your scripting language! What you will learn * Create C++ classes and structs that integrate well with UE4 and the Blueprints editor * Discover how to work with various APIs that Unreal Engine already contains * Utilize advanced concepts such as events, delegates, and interfaces in your UE4 projects * Build user interfaces using Canvas and UMG through C++ * Extend the Unreal Editor by creating custom windows and editors * Implement AI tasks and services using C++, Blackboard, and Behavior Trees * Write C++ code with networking in mind and replicate properties and functions Who this book is for If you are really passionate game developer looking for solutions to common scripting problems, then this is the book for you. Understanding of the fundamentals of game design and C++ is expected to get the most from this book.

Your one stop guide to automating infrastructure security using DevOps and DevSecOps Key Features * Secure and automate techniques to protect web, mobile or cloud services * Automate secure code inspection in C++, Java, Python, and JavaScript * Integrate security testing with automation frameworks like fuzz, BDD, Selenium and Robot Framework Book Description Security automation is the automatic handling of software security assessments tasks. This book helps you to build your security automation framework to scan for vulnerabilities without human intervention. This book will teach you to adopt security automation techniques to continuously improve your entire software development and security testing. You will learn to use open source tools and techniques to integrate security testing tools directly into your CI/CD framework. With this book, you will see how to implement security inspection at every layer, such as secure code inspection, fuzz testing, Rest API, privacy, infrastructure security, and web UI testing. With the help of practical examples, this book will teach you to implement the combination of automation and Security in DevOps. You will learn about the integration of security testing results for an overall security status for projects. By the end of this book, you will be confident implementing automation security in all layers of your software development stages and will be able to build your own in-house security automation platform throughout your mobile and cloud releases. What you will learn * Automate secure code inspection with open source tools and effective secure code scanning suggestions * Apply security testing tools and automation frameworks to identify security vulnerabilities in web, mobile and cloud services * Integrate security testing tools such as OWASP ZAP, NMAP, SSLyze, SQLMap, and OpenSCAP * Implement automation testing techniques with Selenium, JMeter, Robot Framework, Gauntlt, BDD, DDT, and Python unittest * Execute security testing of a Rest API Implement web application security with open source tools and script templates for CI/CD integration * Integrate various types of security testing tool results from a single project into one dashboard Who this book is for The book is for software developers, architects, testers and QA engineers who are looking to leverage automated security testing techniques.

This fast-paced guide will quickly enhance your skills to develop a highly scalable Cloud environment About This Book ? Efficiently build a highly scalable and reliable cloud environment for your applications with AWS ? Leverage the various AWS components and services to build a secure, reliable, and robust environment to host your applications on ? This quick-start guide will quickly enhance your skills to develop highly scalable services Who This Book Is For This book is for IT professionals and system administrators looking to design, deploy, and manage your applications and services on the AWS cloud platform. It’s also ideal for developers looking to build highly scalable cloud-based services. A basic understanding of AWS would be beneficial. What You Will Learn ? Find out about IAM to access AWS services securely ? Explore EC2 (virtual server) and scale up/down your application based on heavy traffic ? Learn about unlimited data storage service S3 and host a static website within minutes ? Get to grips with Relational Databases and NoSQL databases under the AWS ecosystem ? Understand the caching mechanism ? Get to know about notifications service and monitor AWS services ? Secure and troubleshoot your AWS architecture In Detail AWS is at the forefront of Cloud Computing today. Businesses are adopting AWS Cloud because of its reliability, versatility, and flexible design. The main focus of this book is teaching you how to build and manage highly reliable and scalable applications and services on AWS. It will provide you with all the necessary skills to design, deploy, and manage your applications and services on the AWS cloud platform. We’ll start by exploring Amazon S3, EC2, and so on to get you well-versed with core Amazon services. Moving on, we’ll teach you how to design and deploy highly scalable and optimized workloads. You’ll also discover easy-to-follow, hands-on steps, tips, and recommendations throughout the book and get to know essential security and troubleshooting concepts. By the end of the book, you’ll be able to create a highly secure, fault tolerant, and scalable environment for your applications to run on. Style and approach This book is all about fast and intensive learning. That means we don’t waste time helping you get started. The new features provided by AWS resources are being covered with highly-effective examples to develop new things, demonstrating different ways to create and use the AWS resources efficiently.

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow v1.7. About This Book ? Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow v1.7 ? Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ? Gain real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ? Apply deep machine intelligence and GPU computing with TensorFlow v1.7 ? Access public datasets and use TensorFlow to load, process, and transform the data ? Discover how to use the high-level TensorFlow API to build more powerful applications ? Use deep learning for scalable object detection and mobile computing ? Train machines quickly to learn from data by exploring reinforcement learning techniques ? Explore active areas of deep learning research and applications In Detail Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow v1.7, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. Style and approach This step-by-step guide explores common, and not so common, deep neural networks, and shows how they can be exploited in the real world with complex raw data. Benefit from practical examples, and learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing.

Develop rich and scalable web applications with Node.js, Express.js, and MongoDB About This Book ? Learn the advanced features of Aurelia to build responsive web applications ? Write clean, modular, and testable code that will be easy to maintain and evolve ? Harness the power of JavaScript on the client and server side to build full-stack applications Who This Book Is For Hands-On Full Stack Web Development with Aurelia is for you if you are a web or full-stack JavaScript developer who has experience with traditional stacks such as LAMP, MEAN, or MERN and wish to explore the power of Aurelia and new stack with modern web technologies. What You Will Learn ? Employ best practices and modern approaches to create frontend applications ? Learn about modern CSS preprocessors and improve the readability of your application ? Use the Aurelia framework to create navigable web applications ? Write your own tests, making your application secure and fault-tolerant ? Create solid RESTful APIs using the microservice architecture ? Understand the NoSQL paradigm and get the best performance from your database ? Integrate third-party libraries such as Gmail for Single Sign On ? Write UI testing scripts and integration tests to build extensible apps In Detail Hands-On Full Stack Web Development with Aurelia begins with a review of basic JavaScript concepts and the structure of an Aurelia application generated with the Aurelia-CLI tool. You will learn how to create interesting and intuitive application using the Aurelia-Materialize plugin, which implements the material design approach. Once you fully configure a FIFA World Cup 2018 app, you'll start creating the initial components through TDD practices and then develop backend services to process and store all the user data. This book lets you explore the NoSQL model and implement it using one of the most popular NoSQL databases, MongoDB, with some exciting libraries to make the experience effortless. You'll also be able to add some advanced behavior to your components, from managing the lifecycle properly to using dynamic binding, field validations, and the custom service layer. You will integrate your application with Google OAuth Service and learn best practices to secure your applications. Furthermore, you'll write UI Testing scripts to create high-quality Aurelia Apps and explore the most used tools to run end-to-end tests. In the concluding chapters, you'll be able to deploy your application to the Cloud and Docker containers. By the end of this book, you will have learned how to create rich applications using best practices and modern approaches. Style and approach This is a comprehensive example-based book that guides you to create highly scalable applications using the new MEAN Stack.

Get a solid understanding of Java fundamentals to master programming through a series of practical steps About This Book ? Enjoy your first step into the world of programming ? Understand what a language is and use its features to build applications ? Learn about a wide variety of programming applications Who This Book Is For Introduction to Programming is for anybody who wants to learn programming. All you’ll need is a computer, internet connection, and a cup of coffee. What You Will Learn ? Understand what Java is ? Install Java and learn how to run it ? Write and execute a Java program ? Write and execute the test for your program ? Install components and confgure your development environment ? Learn and use Java language fundamentals ? Learn object-oriented design principles ? Master the frequently used Java constructs In Detail Have you ever thought about making your computer do what you want it to do? Do you want to learn to program, but just don't know where to start? Instead of guiding you in the right direction, have other learning resources got you confused with over-explanations? Don't worry. Look no further. Introduction to Programming is here to help. Written by an industry expert who understands the challenges faced by those from a non-programming background, this book takes a gentle, hand-holding approach to introducing you to the world of programming. Beginning with an introduction to what programming is, you'll go on to learn about languages, their syntax, and development environments. With plenty of examples for you to code alongside reading, the book's practical approach will help you to grasp everything it has to offer. More importantly, you'll understand several aspects of application development. As a result, you'll have your very own application running by the end of the book. To help you comprehensively understand Java programming, there are exercises at the end of each chapter to keep things interesting and encourage you to add your own personal touch to the code and, ultimately, your application. Style and approach This step-by-step guide will familiarize you with programming using some practical examples.

Discover solutions to all your Tkinter and Python GUI development problems About This Book ? Integrate efficient Python GUI programming techniques with Tkinter ? Efficiently implement advanced MVC architectures in your Python GUI apps ? Solve all your problems related to Tkinter and Python GUI development Who This Book Is For This book is for Python developers who are familiar with the basics of the language syntax, data structures, and OOP. You do not need previous experience with Tkinter or other GUI development libraries. What You Will Learn ? Add widgets and handle user events ? Lay out widgets within windows using frames and the different geometry managers ? Configure widgets so that they have a customized appearance and behavior ? Improve the navigation of your apps with menus and dialogs ? Apply object-oriented programming techniques in Tkinter applications ? Use threads to achieve responsiveness and update the GUI ? Explore the capabilities of the canvas widget and the types of items that can be added to it ? Extend Tkinter applications with the TTK (themed Tkinter) module In Detail As one of the more versatile programming languages, Python is well-known for its batteries-included philosophy, which includes a rich set of modules in its standard library; Tkinter is the library included for building desktop applications. Due to this, Tkinter is a common choice for rapid GUI development, and more complex applications can benefit from the full capabilities of this library. This book covers all of your Tkinter and Python GUI development problems and solutions. Tkinter GUI Application Development Cookbook starts with an overview of Tkinter classes and at the same time provides recipes for basic topics, such as layout patterns and event handling. Next, we cover how to develop common GUI patterns, such as entering and saving data, navigating through menus and dialogs, and performing long-running actions in the background. You will then make your apps leverage network resources effectively, perform 2D and 3D animation-related tasks, create 3D objects, and perform advanced graphical operations. Finally, this book covers using the canvas and themed widgets. By the end of the book, you will have an in-depth knowledge of Tkinter classes, and will know how to use them to build efficient and rich GUI applications. Style and approach A practical recipe-based guide that will help you find solutions to all your Tkinter and Python GUI development-related problems.

Learn how to execute web application penetration testing end-to-end About This Book ? Build an end-to-end threat model landscape for web application security ? Learn both web application vulnerabilities and web intrusion testing ? Associate network vulnerabilities with a web application infrastructure Who This Book Is For Practical Web Penetration Testing is for you if you are a security professional, penetration tester, or stakeholder who wants to execute penetration testing using the latest and most popular tools. Basic knowledge of ethical hacking would be an added advantage. What You Will Learn ? Learn how to use Burp Suite effectively ? Use Nmap, Metasploit, and more tools for network infrastructure tests ? Practice using all web application hacking tools for intrusion tests using Kali Linux ? Learn how to analyze a web application using application threat modeling ? Know how to conduct web intrusion tests ? Understand how to execute network infrastructure tests ? Master automation of penetration testing functions for maximum efficiency using Python In Detail Companies all over the world want to hire professionals dedicated to application security. Practical Web Penetration Testing focuses on this very trend, teaching you how to conduct application security testing using real-life scenarios. To start with, you’ll set up an environment to perform web application penetration testing. You will then explore different penetration testing concepts such as threat modeling, intrusion test, infrastructure security threat, and more, in combination with advanced concepts such as Python scripting for automation. Once you are done learning the basics, you will discover end-to-end implementation of tools such as Metasploit, Burp Suite, and Kali Linux. Many companies deliver projects into production by using either Agile or Waterfall methodology. This book shows you how to assist any company with their SDLC approach and helps you on your journey to becoming an application security specialist. By the end of this book, you will have hands-on knowledge of using different tools for penetration testing. Style and approach In this book, you will learn and understand the workflow of application security testing. Starting from analysis using threat modeling until the testing phase and before the web project goes into production, you will be able conduct effective penetrating testing using web intrusion tests , network infrastructure tests, and code review.

Learn how to automate and manage your containers and reduce the overall operation burden on your system. About This Book ? Use containers to manage, scale and orchestrate apps in your organization ? Transform the latest concept of Kubernetes 1.10 into examples ? Expert techniques for orchestrating containers effectively Who This Book Is For This book is for system administrators, developers, DevOps engineers, or any stakeholder who wants to understand how Kubernetes works using a recipe-based approach. Basic knowledge of Kubernetes and Containers is required. What You Will Learn ? Build your own container cluster ? Deploy and manage highly scalable, containerized applications with Kubernetes ? Build high-availability Kubernetes clusters ? Build a continuous delivery pipeline for your application ? Track metrics and logs for every container running in your cluster ? Streamline the way you deploy and manage your applications with large-scale container orchestration In Detail Kubernetes is an open source orchestration platform to manage containers in a cluster environment. With Kubernetes, you can configure and deploy containerized applications easily. This book gives you a quick brush up on how Kubernetes works with containers, and an overview of main Kubernetes concepts, such as Pods, Deployments, Services and etc. This book explains how to create Kubernetes clusters and run applications with proper authentication and authorization configurations. With real-world recipes, you'll learn how to create high availability Kubernetes clusters on AWS, GCP and in on-premise datacenters with proper logging and monitoring setup. You'll also learn some useful tips about how to build a continuous delivery pipeline for your application. Upon completion of this book, you will be able to use Kubernetes in production and will have a better understanding of how to manage containers using Kubernetes. Style and approach This recipe-based book will teach you how to use Kubernetes in production and will help you discover various steps involved in managing your containers using Kubernetes

Become a better web programmer by writing efficient and modular code using ES6 and ES8 About This Book ? Learn to write asynchronous code and improve the readability of your web applications ? Explore advanced concepts such as closures, Proxy, generators, Promise, async functions, and Atomics ? Use different design patterns to create structures to solve common organizational and processing issues Who This Book Is For If you’re a web developer with a basic understanding of JavaScript and wish to learn the latest features of ECMAScript for developing efficient web applications, this book is for you. What You Will Learn ? Organize JavaScript programs across multiple files, using ES modules ? Create and work with promises using the Promise object and methods ? Compose async functions to propagate and handle errors ? Solve organizational and processing issues with structures using design patterns ? Use classes to encapsulate and share behavior ? Orchestrate parallel programs using WebWorkers, SharedMemory, and Atomics ? Use and extend Map, Set, and Symbol to work with user-defined classes and simulate data types ? Explore new array methods to avoid looping with arrays and other collections In Detail ECMAScript Cookbook follows a modular approach with independent recipes covering different feature sets and specifications of ECMAScript to help you become an efficient programmer. This book starts off with organizing your JavaScript applications as well as delivering those applications to modem and legacy systems. You will get acquainted with features of ECMAScript 8 such as async, SharedArrayBuffers, and Atomic operations that enhance asynchronous and parallel operations. In addition to this, this book will introduce you to SharedArrayBuffers, which allow web workers to share data directly, and Atomic operations, which help coordinate behavior across the threads. You will also work with OOP and Collections, followed by new functions and methods on the built-in Object and Array types that make common operations more manageable and less error-prone. You will then see how to easily build more sophisticated and expressive program structures with classes and inheritance. In the end, we will cover Sets, Maps, and Symbols, which are the new types introduced in ECMAScript 6 to add new behaviors and allow you to create simple and powerful modules. By the end of the book, you will be able to produce more efficient, expressive, and simpler programs using the new features of ECMAScript. Style and approach This book will follow a modular approach covering independent recipes on different features of ECMAScript throughout the book.

A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop About This Book ? Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform ? Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more ? A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Who This Book Is For This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book. What You Will Learn ? Build an efficient enterprise Big Data strategy centered around Apache Hadoop ? Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more ? Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari ? Design effective streaming data pipelines and build your own enterprise search solutions ? Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset ? Plan, set up and administer your Hadoop cluster efficiently In Detail The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. Style and approach Comprehensive guide with a perfect blend of theory, examples and implementation of real-world use-cases

Practical, hands-on solutions in Python to overcome any problem in Machine Learning About This Book ? Master the advanced concepts, methodologies, and use cases of machine learning ? Build ML applications for analytics, NLP and computer vision domains ? Solve the most common problems in building machine learning models Who This Book Is For This book is for the intermediate users such as machine learning engineers, data engineers, data scientists, and more, who want to solve simple to complex machine learning problems in their day-to-day work and build powerful and efficient machine learning models. A basic understanding of the machine learning concepts and some experience with Python programming is all you need to get started with this book. What You Will Learn ? Select the right algorithm to derive the best solution in ML domains ? Perform predictive analysis effciently using ML algorithms ? Predict stock prices using the stock index value ? Perform customer analytics for an e-commerce platform ? Build recommendation engines for various domains ? Build NLP applications for the health domain ? Build language generation applications using different NLP techniques ? Build computer vision applications such as facial emotion recognition In Detail Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions. In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity. Style and approach This book is a step-by-step guide on how to develop machine learning applications for various domains. Each chapter of this book contains the practical guide on how to build specific machine learning applications from its base-line approach to the best possible approach. Basic necessary concepts, conman mistakes for every approach and optimization techniques are discussed for each application.

Build rich and collaborative applications using client-side code with React, Redux, and Firebase About This Book ? A practical guide covering the full stack for web development with React 16 and Firebase ? Leverage the power of Firebase Cloud Storage, messaging, functions, OAuth, and database security to develop serverless web applications. ? Develop high-performance applications without the hassle of setting up complex web infrastructure. Who This Book Is For This book is for JavaScript developers who have some previous knowledge of React and want to develop serverless, full-stack applications but without the hassle of setting up a complex infrastructure. What You Will Learn ? Install powerful React.js and Firebase tools to make development much more efficient ? Create React components with Firebase to save and retrieve the data in real-time ? Use Firebase Authentication to make your React user interface secure ? Develop React and Firebase applications with Redux integration ? Firebase database security rules ? Firebase Cloud Storage Integration to upload and store data on the cloud ? Create a complete real-time application with React and firebase ? Using Firebase Cloud messaging and Cloud functions with React ? Firebase Cloud Storage integration with React In Detail ReactJS is a wonderful framework for UI development. Firebase as a backend with React is a great choice as it is easy, powerful, and provides great developer experience. It removes a lot of boilerplate code from your app and allows you to focus on your app to get it out quickly to users. Firebase with React is also a good choice for Most Viable Product (MVP) development. This book provides more practical insights rather than just theoretical concepts and includes basic to advanced examples – from hello world to a real-time seat booking app and Helpdesk application This book will cover the essentials of Firebase and React.js and will take you on a fast-paced journey through building real-time applications with Firebase features such as Cloud Storage, Cloud Function, Hosting and the Realtime Database. We will learn how to secure our application by using Firebase authentication and database security rules. We will leverage the power of Redux to organize data in the front-end, since Redux attempts to make state mutations predictable by imposing certain restrictions on how and when updates can happen. Towards the end of the book you will have improved your React skills by realizing the potential of Firebase to create real-time serverless web applications. Style and approach Practical insights rather than just theoretical concepts while including basic to advanced examples – from hello world to a real-time seat booking app and Helpdesk application.

Enhance your software deployment workflow using containers About This Book ? Get up-and-running with basic to advanced concepts of Docker ? Get acquainted with concepts such as Docker containers, Docker images, orchestrators and so on. ? Practical test-based approach to learning a prominent containerization tool Who This Book Is For This book is targeted at system administrators, operations engineers, DevOps engineers, and developers or stakeholders who are interested in getting started with Docker from scratch. No prior experience with Docker Containers is required. What You Will Learn ? Containerize your traditional or microservice-based application ? Share or ship your application as an immutable container image ? Build a Docker swarm and a Kubernetes cluster in the cloud ? Run a highly distributed application using Docker Swarm or Kubernetes ? Update or rollback a distributed application with zero downtime ? Secure your applications via encapsulation, networks, and secrets ? Know your options when deploying your containerized app into the cloud In Detail Docker containers have revolutionized the software supply chain in small and big enterprises. Never before has a new technology so rapidly penetrated the top 500 enterprises worldwide. Companies that embrace containers and containerize their traditional mission-critical applications have reported savings of at least 50% in total maintenance cost and a reduction of 90% (or more) of the time required to deploy new versions of those applications. Furthermore they are benefitting from increased security just by using containers as opposed to running applications outside containers. This book starts from scratch, introducing you to Docker fundamentals and setting up an environment to work with it. Then we delve into concepts such as Docker containers, Docker images, Docker Compose, and so on. We will also cover the concepts of deployment, orchestration, networking, and security. Furthermore, we explain Docker functionalities on public clouds such as AWS. By the end of this book, you will have hands-on experience working with Docker containers and orchestrators such as SwarmKit and Kubernetes. Style and approach The simple end-to-end guide will help you learn everything about how to containerize, ship, and run both a traditional application and a modern microservice-based application on-premise or in the cloud.

Combine the power of analytics and cloud computing for faster and efficient insights About This Book ? Master the concept of analytics on the cloud: and how organizations are using it ? Learn the design considerations and while applying a cloud analytics solution ? Design an end-to-end analytics pipeline on the cloud Who This Book Is For This book is targeted at CIOs, CTOs, and even analytics professionals looking for various alternatives to implement their analytics pipeline on the cloud. Data professionals looking to get started with cloud-based analytics will also find this book useful. Some basic exposure to cloud platforms such as GCP will be helpful, but not mandatory. What You Will Learn ? Explore the basics of cloud analytics and the major cloud solutions ? Learn how organizations are using cloud analytics to improve the ROI ? Explore the design considerations while adopting cloud services ? Work with the ingestion and storage tools of GCP such as Cloud Pub/Sub ? Process your data with tools such as Cloud Dataproc, BigQuery, etc ? Over 70 GCP tools to build an analytics engine for cloud analytics ? Implement machine learning and other AI techniques on GCP In Detail With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation Style and approach Comprehensive guide with a perfect blend of theory, examples, and implementation of real-world use-cases

Build applications and infrastructures that leverage Function-as-a-Service and Docker About This Book ? Implement containerization in Serverless/FaaS environments ? Utilize Docker as a functional unit of work for Serverless/FaaS platforms ? Use Docker as a portable infrastructure for Serverless Applications Who This Book Is For If you are a Developer, a Docker Engineer, a DevOps Engineer, or any stakeholder interested in learning the use of Docker on Serverless environments then this book is for you. What You Will Learn ? Learn what Serverless and FaaS applications are ? Get acquainted with the architectures of three major serverless systems ? Explore how Docker technologies can help develop Serverless applications ? Create and maintain FaaS infrastructures ? Set up Docker infrastructures to serve as on-premises FaaS infrastructures ? Define functions for Serverless applications with Docker containers In Detail Serverless applications have gained a lot of popularity among developers and are currently the buzzwords in the tech market. Docker and serverless are two terms that go hand-in-hand. This book will start by explaining serverless and Function-as-a-Service (FaaS) concepts, and why they are important. Then, it will introduce the concepts of containerization and how Docker fits into the Serverless ideology. It will explore the architectures and components of three major Docker-based FaaS platforms, how to deploy and how to use their CLI. Then, this book will discuss how to set up and operate a production-grade Docker cluster. We will cover all concepts of FaaS frameworks with practical use cases, followed by deploying and orchestrating these serverless systems using Docker. Finally, we will also explore advanced topics and prototypes for FaaS architectures in the last chapter. By the end of this book, you will be in a position to build and deploy your own FaaS platform using Docker. Style and approach A practical guide that offers a simple way to easily understand Serverless Applications utilizing Docker as the development environment.

Learn to use AWS IoT services to build your connected applications with the help of this comprehensive guide. About This Book ? Gets you started with AWS IoT and its functionalities ? Learn different modules of AWS IoT with practical use cases. ? Learn to secure your IoT communication Who This Book Is For This book is for anyone who wants to get started with the AWS IoT Suite and implement it with practical use cases. This book acts as an extensive guide, on completion of which you will be in a position to start building IoT projects using AWS IoT platform and using cloud services for your projects. What You Will Learn ? Implement AWS IoT on IoT projects ? Learn the technical capabilities of AWS IoT and IoT devices ? Create IoT-based AWS IoT projects ? Choose IoT devices and AWS IoT platforms to use based on the kind of project you need to build ? Deploy AWS Greengrass and AWS Lambda ? Develop program for AWS IoT Button ? Visualize IoT AWS data ? Build predictive analytics using AWS IoT and AWS Machine Learning In Detail The Internet of Things market increased a lot in the past few years and IoT development and its adoption have showed an upward trend. Analysis and predictions say that Enterprise IoT platforms are the future of IoT. AWS IoT is currently leading the market with its wide range of device support SDKs and versatile management console. This book initially introduces you to the IoT platforms, and how it makes our IoT development easy. It then covers the complete AWS IoT Suite and how it can be used to develop secure communication between internet-connected things such as sensors, actuators, embedded devices, smart applications, and so on. The book also covers the various modules of AWS: AWS Greengrass, AWS device SDKs, AWS IoT Platform, AWS Button, AWS Management consoles, AWS-related CLI, and API references, all with practical use cases. Near the end, the book supplies security-related best practices to make bi-directional communication more secure. When you've finished this book, you'll be up-and-running with the AWS IoT Suite, and building IoT projects. Style and approach This book is a step-by-step practical guide that helps you learn AWS IoT quickly.

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