Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features * Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more * Build your own neural network models using modern Python libraries * Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn * Use cluster algorithms to identify and optimize natural groups of data * Explore advanced non-linear and hierarchical clustering in action * Soft label assignments for fuzzy c-means and Gaussian mixture models * Detect anomalies through density estimation * Perform principal component analysis using neural network models * Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.

Explore various Azure services to build solutions that leverage effective design patterns Key Features *Create, deploy, and host cloud applications on Azure *Understand various Azure services that help you host serverless applications *Explore practical examples to help you secure and troubleshoot your cloud environment Book Description Azure is one of the leading public cloud service providers. Thanks to a number of Azure service updates, it continues to make advances in the realm of cloud computing. Learn Microsoft Azure starts with the fundamentals of cloud computing. You will learn to configure and set up the Azure infrastructure. As you make your way through the book, you'll explore Azure services, along with working on virtual memory systems (VMS) and deployment models. You will understand various services in the Azure ecosystem, such as Azure IoT and Azure Analytics, among others. An easy-to-follow introduction to various cloud design patterns will also add to your efficiency in designing cloud solutions. In the concluding chapters, you'll secure your virtual networks using Network security groups and configure Azure Active Directory (Azure AD) to set a custom domain name and company profile. By the end of this book, you will have learned to secure and troubleshoot your Azure cloud environment and be fully aware of best practices for Azure cloud administration. What you will learn *Understand the cloud services offered by Azure *Design storage and networks in Azure for your Azure VM *Work with web apps and Azure SQL databases *Build your identity management solutions on Azure using Azure AD *Monitor, protect, and automate your Azure services using Operation Management Suite (OMS) *Implement OMS for Azure services Who this book is for Learn Microsoft Azure is for administrators, cloud engineers, and developers who want to get started with using Azure as their cloud platform and build cloud-based applications for their enterprises.

Get into the world of smart data security using machine learning algorithms and Python libraries Key Features *Learn machine learning algorithms and cybersecurity fundamentals *Automate your daily workflow by applying use cases to many facets of security *Implement smart machine learning solutions to detect various cybersecurity problems Book Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learn *Use machine learning algorithms with complex datasets to implement cybersecurity concepts *Implement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problems *Learn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDA *Understand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimes *Use TensorFlow in the cybersecurity domain and implement real-world examples *Learn how machine learning and Python can be used in complex cyber issues Who this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

Over 100 recipes to get up and running with the modern Linux administration ecosystem Key Features *Understand and implement the core system administration tasks in Linux *Discover tools and techniques to troubleshoot your Linux system *Maintain a healthy system with good security and backup practices Book Description Linux is one of the most widely used operating systems among system administrators,and even modern application and server development is heavily reliant on the Linux platform. The Linux Administration Cookbook is your go-to guide to get started on your Linux journey. It will help you understand what that strange little server is doing in the corner of your office, what the mysterious virtual machine languishing in Azure is crunching through, what that circuit-board-like thing is doing under your office TV, and why the LEDs on it are blinking rapidly. This book will get you started with administering Linux, giving you the knowledge and tools you need to troubleshoot day-to-day problems, ranging from a Raspberry Pi to a server in Azure, while giving you a good understanding of the fundamentals of how GNU/Linux works. Through the course of the book, you’ll install and configure a system, while the author regales you with errors and anecdotes from his vast experience as a data center hardware engineer, systems administrator, and DevOps consultant. By the end of the book, you will have gained practical knowledge of Linux, which will serve as a bedrock for learning Linux administration and aid you in your Linux journey. What you will learn *Install and manage a Linux server, both locally and in the cloud *Understand how to perform administration across all Linux distros *Work through evolving concepts such as IaaS versus PaaS, containers, and automation *Explore security and configuration best practices *Troubleshoot your system if something goes wrong *Discover and mitigate hardware issues, such as faulty memory and failing drives Who this book is for If you are a system engineer or system administrator with basic experience of working with Linux, this book is for you.

Explore various Generative Adversarial Network architectures using the Python ecosystem Key Features * Use different datasets to build advanced projects in the Generative Adversarial Network domain * Implement projects ranging from generating 3D shapes to a face aging application * Explore the power of GANs to contribute in open source research and projects Book Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learn * Train a network on the 3D ShapeNet dataset to generate realistic shapes * Generate anime characters using the Keras implementation of DCGAN * Implement an SRGAN network to generate high-resolution images * Train Age-cGAN on Wiki-Cropped images to improve face verification * Use Conditional GANs for image-to-image translation * Understand the generator and discriminator implementations of StackGAN in Keras Who this book is for If you’re a data scientist, machine learning developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.

A comprehensive guide in developing and deploying high performance microservices with Rust Key Features * Start your microservices journey and get a broader perspective on microservices development using RUST 2018, * Build, deploy, and test microservices using AWS * Explore advanced techniques for developing microservices such as actor model, Requests Routing, and threads Book Description Microservice architecture is sweeping the world as the de facto pattern for building web-based applications. Rust is a language particularly well-suited for building microservices. It is a new system programming language that offers a practical and safe alternative to C. This book describes web development using the Rust programming language and will get you up and running with modern web frameworks and crates with examples of RESTful microservices creation. You will deep dive into Reactive programming, and asynchronous programming, and split your web application into a set of concurrent actors. The book provides several HTTP-handling examples with manageable memory allocations. You will walk through stateless high-performance microservices, which are ideally suitable for computation or caching tasks, and look at stateful microservices, which are filled with persistent data and database interactions. As we move along, you will learn how to use Rust macros to describe business or protocol entities of our application and compile them into native structs, which will be performed at full speed with the help of the server's CPU. Finally, you will be taken through examples of how to test and debug microservices and pack them into a tiny monolithic binary or put them into a container and deploy them to modern cloud platforms such as AWS. What you will learn * Get acquainted with leveraging Rust web programming * Get to grips with various Rust crates, such as hyper, Tokio, and Actix * Explore RESTful microservices with Rust * Understand how to pack Rust code to a container using Docker * Familiarize yourself with Reactive microservices * Deploy your microservices to modern cloud platforms such as AWS Who this book is for This book is for developers who have basic knowledge of RUST, and want to learn how to build, test, scale, and manage RUST microservices. No prior experience of writing microservices in RUST is assumed.

Begin your iOS 12 app development journey with this practical guide Key Features *Kick-start your iOS programming career and have fun building iOS apps of your choice *Get to grips with Xcode 10 and Swift 4.2, the building blocks of iOS development *Discover the latest features of iOS 12 - SiriKit, notifications, and much more Book Description Want to build iOS 12 applications from scratch with the latest Swift 4.2 language and Xcode 10 by your side? Forget sifting through tutorials and blog posts; this book is a direct route to iOS development, taking you through the basics and showing you how to put principles into practice. Take advantage of this developer-friendly guide and start building applications that may just take the App Store by storm! If you’re already an experienced programmer, you can jump right in and learn the latest iOS 12 features. For beginners, this book starts by introducing you to iOS development as you learn Xcode and Swift. You'll also study advanced iOS design topics, such as gestures and animations, to give your app the edge. You’ll explore the latest Swift 4.2 and iOS 12 developments by incorporating new features, such as the latest in notifications, custom-UI notifications, maps, and the recent additions in Sirikit. The book will guide you in using TestFlight to quickly get to grips with everything you need to get your project on the App Store. By the end of this book, you'll be ready to start building your own cool iOS applications confidently. What you will learn *Explore the distinctive design principles that define the iOS user experience *Navigate panels within an Xcode project *Use the latest Xcode asset catalogue of Xcode 10 *Create a playgrounds project within your projects and understand how Ranges and Control flow work *Study operations with integers and work your way through if statements *Build a responsive UI and add privacy to your custom-rich notifications *Set up Sirikit to add voice for Siri shortcuts *Collect valuable feedback with TestFlight before releasing your apps on the App Store Who this book is for This book is for you if you are completely new to Swift, iOS, or programming and want to make iOS applications. However, you’ll also find this book useful if you’re an experienced programmer looking to explore the latest iOS 12 features.

Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features *Understand the common architecture of different types of GANs *Train, optimize, and deploy GAN applications using TensorFlow and Keras *Build generative models with real-world data sets, including 2D and 3D data Book Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learn *Structure a GAN architecture in pseudocode *Understand the common architecture for each of the GAN models you will build *Implement different GAN architectures in TensorFlow and Keras *Use different datasets to enable neural network functionality in GAN models *Combine different GAN models and learn how to fine-tune them *Produce a model that can take 2D images and produce 3D models *Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key Features *Work with powerful open-source libraries for data wrangling, analysis, and visualization *Develop full-featured, full-stack web applications *Learn to perform supervised and unsupervised machine learning and time series analysis with Julia Book Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learn *Leverage Julia's strengths, its top packages, and main IDE options *Analyze and manipulate datasets using Julia and DataFrames *Write complex code while building real-life Julia applications *Develop and run a web app using Julia and the HTTP package *Build a recommender system using supervised machine learning *Perform exploratory data analysis *Apply unsupervised machine learning algorithms *Perform time series data analysis, visualization, and forecasting Who this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

Find out how to write Kotlin code without overhead and how to use different profiling tools and bytecode viewer to inspect expressions of Kotlin language. About This Book ? Apply modern Kotlin features to speed up processing and implement highly efficient and reliable codes. ? Learn memory optimization, concurrency, multi-threading, scaling, and caching techniques to achieve high performance. ? Learn how to prevent unnecessary overhead and use profiling tools to detect performance issues. Who This Book Is For This book is for Kotlin developers who would like to build reliable and high-performance applications. Prior Kotlin programming knowledge is assumed. What You Will Learn ? Understand the importance of high performance ? Learn performance metrics ? Learn popular design patterns currently being used in Kotlin ? Understand how to apply modern Kotlin features to data processing ? Learn how to use profling tools ? Discover how to read bytecode ? Learn to perform memory optimizations ? Uncover approaches to the multithreading environment In Detail The ease with which we write applications has been increasing, but with it comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day requirement In this book, we explore how to achieve this crucial balance, while developing and deploying applications with Kotlin. The book starts by analyzing various Kotlin specifcations to identify those that have a potentially adverse effect on performance. Then, we move on to monitor techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help to us achieve high performance: memory optimization, concurrency, multi threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. We'll also cover best practices of Kotlin programming that will help you to improve the quality of your code base. By the end of the book, you will have gained some insight into various techniques and solutions that will help to create high-performance applications in the Kotlin environment Style and approach This book guides you through how to use profiling tools to detect performance issues and build high-performance applications in the Kotlin environment.

Get acquainted with GCP and manage robust, highly available, and dynamic solutions to drive business objective About This Book ? Identify the strengths, weaknesses and ideal use-cases for individual services offered on the Google Cloud Platform ? Make intelligent choices about which cloud technology works best for your use-case ? Leverage Google Cloud Platform to analyze and optimize technical and business processes Who This Book Is For If you are a Cloud architect who is responsible to design and manage robust cloud solutions with Google Cloud Platform, then this book is for you. System engineers and Enterprise architects will also find this book useful. A basic understanding of distributed applications would be helpful, although not strictly necessary. Some working experience on other public cloud platforms would help too. What You Will Learn ? Set up GCP account and utilize GCP services using the cloud shell, web console, and client APIs ? Harness the power of App Engine, Compute Engine, Containers on the Kubernetes Engine, and Cloud Functions ? Pick the right managed service for your data needs, choosing intelligently between Datastore, BigTable, and BigQuery ? Migrate existing Hadoop, Spark, and Pig workloads with minimal disruption to your existing data infrastructure, by using Dataproc intelligently ? Derive insights about the health, performance, and availability of cloud-powered applications with the help of monitoring, logging, and diagnostic tools in Stackdriver In Detail Using a public cloud platform was considered risky a decade ago, and unconventional even just a few years ago. Today, however, use of the public cloud is completely mainstream - the norm, rather than the exception. Several leading technology firms, including Google, have built sophisticated cloud platforms, and are locked in a fierce competition for market share. The main goal of this book is to enable you to get the best out of the GCP, and to use it with confidence and competence. You will learn why cloud architectures take the forms that they do, and this will help you become a skilled high-level cloud architect. You will also learn how individual cloud services are configured and used, so that you are never intimidated at having to build it yourself. You will also learn the right way and the right situation in which to use the important GCP services. By the end of this book, you will be able to make the most out of Google Cloud Platform design. Style and approach A clear, concise, and straightforward book which will enable to develop and manage optimum solutions for your infrastructure

Run Ansible playbooks to launch complex multi-tier applications hosted in public clouds About This Book ? Build your learning curve using Ansible ? Automate cloud, network, and security infrastructures with ease ? Gain hands-on exposure on Ansible Who This Book Is For Learn Ansible is perfect for system administrators and developers who want to take their current workflows and transform them into repeatable playbooks using Ansible. No prior knowledge of Ansible is required. What You Will Learn ? Write your own playbooks to configure servers running CentOS, Ubuntu, and Windows ? Identify repeatable tasks and write playbooks to automate them ? Define a highly available public cloud infrastructure in code, making it easy to distribute your infrastructure configuration ? Deploy and configure Ansible Tower and Ansible AWX ? Learn to use community contributed roles ? Use Ansible in your day-to-day role and projects In Detail Ansible has grown from a small, open source orchestration tool to a full-blown orchestration and configuration management tool owned by Red Hat. Its powerful core modules cover a wide range of infrastructures, including on-premises systems and public clouds, operating systems, devices, and services—meaning it can be used to manage pretty much your entire end-to-end environment. Trends and surveys say that Ansible is the first choice of tool among system administrators as it is so easy to use. This end-to-end, practical guide will take you on a learning curve from beginner to pro. You'll start by installing and configuring the Ansible to perform various automation tasks. Then, we'll dive deep into the various facets of infrastructure, such as cloud, compute and network infrastructure along with security. By the end of this book, you'll have an end-to-end understanding of Ansible and how you can apply it to your own environments. Style and approach A hands-on approach to give you practical experience of writing playbooks and roles and executing them. At the end of each chapter, you’ll find test questions to test your knowledge on Ansible.

Complement Selenium with useful additions that fit seamlessly into the rich and well-crafted API that Selenium offers About This Book ? Understand the power, simplicity, and limitations of the core Selenium framework ? Write clear, readable, and reliable tests that perform complex test automation tasks ? Work with ChromeDriver and GeckoDriver in headless mode Who This Book Is For If you are a software tester or a developer with working experience in Selenium and competency with Java, who is interested in automation and are looking forward to taking the next step in their learning journey, then this is the book for you. What You Will Learn ? Provide fast, useful feedback with screenshots ? Create extensible, well-composed page objects ? Utilize ChromeDriver and GeckoDriver in headless mode ? Leverage the full power of Advanced User Interactions APIs ? Use JavascriptExecutor to execute JavaScript snippets in the browser through Selenium ? Build user interaction into your test script using JavascriptExecutor ? Learn the basics of working with Appium In Detail The second edition of Mastering Selenium 3.0 WebDriver starts by showing you how to build your own Selenium framework with Maven. You'll then look at how you can solve the difficult problems that you will undoubtedly come across as you start using Selenium in an enterprise environment and learn how to produce the right feedback when failing. Next, you’ll explore common exceptions that you will come across as you use Selenium, the root causes of these exceptions, and how to fix them. Along the way, you’ll use Advanced User Interactions APIs, running any JavaScript you need through Selenium; and learn how to quickly spin up a Selenium Grid using Docker containers. In the concluding chapters, you‘ll work through a series of scenarios that demonstrate how to extend Selenium to work with external libraries and applications so that you can be sure you are using the right tool for the job. Style and approach This book is a pragmatic guide that takes you through the process of creating a test framework with Selenium 3. It then shows you how you can extend this framework to overcome common obstacles that you will come across whilst using Selenium.

Create clean code with Dependency Injection principles About This Book ? Use DI to make your code loosely coupled to manage and test your applications easily on Spring 5 and Google Guice ? Learn the best practices and methodologies to implement DI ? Write more maintainable Java code by decoupling your objects from their implementations Who This Book Is For This book is for Java developers who would like to implement DI in their application. Prior knowledge of the Spring and Guice frameworks and Java programming is assumed. What You Will Learn ? Understand the benefits of DI and fo from a tightly coupled design to a cleaner design organized around dependencies ? See Java 9’s new features and modular framework ? Set up Guice and Spring in an application so that it can be used for DI ? Write integration tests for DI applications ? Use scopes to handle complex application scenarios ? Integrate any third-party library in your DI-enabled application ? Implement Aspect-Oriented Programming to handle common cross-cutting concerns such as logging, authentication, and transactions ? Understand IoC patterns and anti-patterns in DI In Detail Dependency Injection (DI) is a design pattern that allows us to remove the hard-coded dependencies and make our application loosely coupled, extendable, and maintainable. We can implement DI to move the dependency resolution from compile-time to runtime. This book will be your one stop guide to write loosely coupled code using the latest features of Java 9 with frameworks such as Spring 5 and Google Guice. We begin by explaining what DI is and teaching you about IoC containers. Then you’ll learn about object compositions and their role in DI. You’ll find out how to build a modular application and learn how to use DI to focus your efforts on the business logic unique to your application and let the framework handle the infrastructure work to put it all together. Moving on, you’ll gain knowledge of Java 9’s new features and modular framework and how DI works in Java 9. Next, we’ll explore Spring and Guice, the popular frameworks for DI. You’ll see how to define injection keys and configure them at the framework-specific level. After that, you’ll find out about the different types of scopes available in both popular frameworks. You’ll see how to manage dependency of cross-cutting concerns while writing applications through aspect-oriented programming. Towards the end, you’ll learn to integrate any third-party library in your DI-enabled application and explore common pitfalls and recommendations to build a solid application with the help of best practices, patterns, and anti-patterns in DI. Style and approach This book will take an easy-to-understand, step-by-step approach providing hands-on examples at every stage.

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. About This Book ? Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j ? Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way ? Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Who This Book Is For If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful. What You Will Learn ? Apply advanced regression techniques to boost the performance of predictive models ? Use different classification algorithms for business analytics ? Generate trading strategies for Bitcoin and stock trading using ensemble techniques ? Train Deep Neural Networks (DNN) using H2O and Spark ML ? Utilize NLP to build scalable machine learning models ? Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application ? Learn how to use autoencoders to develop a fraud detection application ? Implement LSTM and CNN models using DeepLearning4j and MXNet In Detail Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment. Style and approach Leverage the power of machine learning and deep learning in different domains, giving best practices and tips from a real world case studies and help you to avoid pitfalls and fallacies towards decision making based on predictive analytics with ML models.

Explore and master the most important algorithms for solving complex machine learning problems. About This Book ? Discover high-performing machine learning algorithms and understand how they work in depth. ? One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. ? Master concepts related to algorithm tuning, parameter optimization, and more Who This Book Is For This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide. What You Will Learn ? Explore how a ML model can be trained, optimized, and evaluated ? Understand how to create and learn static and dynamic probabilistic models ? Successfully cluster high-dimensional data and evaluate model accuracy ? Discover how artificial neural networks work and how to train, optimize, and validate them ? Work with Autoencoders and Generative Adversarial Networks ? Apply label spreading and propagation to large datasets ? Explore the most important Reinforcement Learning techniques In Detail Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. Style and approach A hands-on guide filled with real-world examples of popular algorithms used for data science and machine learning

Unleash the power of MERN stack by building diverse web applications using React, Node.js, Express, and MongoDB About This Book ? Create dynamic web applications with the MERN stack ? Leverage the power of React in building interactive and complex user interfaces ? Unlock the potential of Node, Express, and MongoDB to build modern full-stack applications Who This Book Is For Full-Stack React Web Development Projects is for JavaScript developers who have some experience with React, but no previous experience with full-stack development involving Node, Express, and MongoDB, and who want practical guidelines to start building different types of real-world web applications with this stack. What You Will Learn ? Set up your development environment and develop a MERN application ? Implement user authentication and authorization using JSON Web Tokens ? Build a social media application by extending the basic MERN application ? Create an online marketplace application with shopping cart and Stripe payments ? Develop a media streaming application using MongoDB GridFS ? Implement server-side rendering with data to improve SEO ? Set up and use React 360 to develop user interfaces with VR capabilities ? Learn industry best practices to make MERN stack applications reliable and scalable In Detail The benefits of using a full JavaScript stack for web development are undeniable, especially when robust and widely adopted technologies such as React, Node, and Express and are available. Combining the power of React with industry-tested, server-side technologies, such as Node, Express, and MongoDB, creates a diverse array of possibilities when developing real-world web applications. This book guides you through preparing the development environment for MERN stack-based web development, to creating a basic skeleton application and extending it to build four different web applications. These applications include a social media, an online marketplace, a media streaming, and a web-based game application with virtual reality features. While learning to set up the stack and developing a diverse range of applications with this book, you will grasp the inner workings of the MERN stack, extend its capabilities for complex features, and gain actionable knowledge of how to prepare MERN-based applications to meet the growing demands of real-world web applications. Style and approach This book provides practical guidelines on setting up and building MERN stack based applications, while providing further explanations on key concepts and implementations.

Get up-to-date with the finer points of Ubuntu Server using this comprehensive guide About This Book ? A practical easy-to-understand book that will teach you how to deploy, maintain and troubleshoot Ubuntu Server ? Get well-versed with newly-added features in Ubuntu 18.04. ? Learn to manage cutting-edge technologies such as virtualization, containers, Nextcloud and more Who This Book Is For This book is intended for readers with intermediate or advanced-beginner skills with Linux, who would like to learn all about setting up servers with Ubuntu Server. This book assumes that the reader knows the basics of Linux, such as editing configuration files and running basic commands. What You Will Learn ? Manage users, groups, and permissions ? Encrypt and decrypt disks with Linux Unified Key Setup (LUKS) ? Set up SSH for remote access, and connect it to other nodes ? Add, remove, and search for packages ? Use NFS and Samba to share directories with other users ? Get to know techniques for managing Apache and MariaDB ? Explore best practices and troubleshooting techniques ? Get familiar with scripting ? Automate server deployments with Ansible In Detail Ubuntu Server has taken the data centers by storm. Whether you're deploying Ubuntu for a large-scale project or for a small office, it is a stable, customizable, and powerful Linux distribution that leads the way with innovative and cutting-edge features. For both simple and complex server deployments, Ubuntu's flexible nature can be easily adapted to meet to the needs of your organization. With this book as your guide, you will learn all about Ubuntu Server, from initial deployment to creating production-ready resources for your network. The book begins with the concept of user management, group management, and filesystem permissions. Continuing into managing storage volumes, you will learn how to format storage devices, utilize logical volume management, and monitor disk usage. Later, you will learn how to virtualize hosts and applications, which will cover setting up KVM/QEMU, as well as containerization with both Docker and LXD. As the book continues, you will learn how to automate configuration with Ansible, as well as take a look at writing scripts. Lastly, you will explore best practices and troubleshooting techniques when working with Ubuntu Server that are applicable to real-world scenarios. By the end of the book, you will be an expert Ubuntu Server administrator who is well-versed in its advanced concepts. Style and approach This book is an advanced guide that will show readers how to administer, manage, and deploy Ubuntu server and will also provide expert-level knowledge on advanced security and backup techniques.

Understand the benefits of DevOps and continuous delivery and see how they support the agile software development process About This Book ? Learn how DevOps can accelerate your entire software development life cycle ? Improve your organization's performance to ensure the smooth production of software and services ? Get hands-on experience in using efficient DevOps tools to better effect Who This Book Is For If you're a developer or system administrator looking to take on larger responsibilities and understand how the infrastructure that builds today's enterprises works, this is the book for you. This book will also help you greatly if you're an operations worker who would like to better support developers. You do not need any previous knowledge of DevOps to understand the concepts in this book. What You Will Learn ? Understand how all deployment systems fit together to form a larger system ? Set up and familiarize yourself with all the tools you need to be efficient with DevOps ? Design an application suitable for continuous deployment systems with DevOps in mind ? Store and manage your code effectively using Git, Gerrit, Gitlab, and more ? Configure a job to build a sample CRUD application ? Test your code using automated regression testing with Jenkins Selenium ? Deploy your code using tools such as Puppet, Ansible, Palletops, Chef, and Vagrant In Detail DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all code workflows from testing environments to production environments. It stresses cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations. Practical DevOps begins with a quick refresher on DevOps and continuous delivery and quickly moves on to show you how DevOps affects software architectures. You'll create a sample enterprise Java application that you’'ll continue to work with through the remaining chapters. Following this, you will explore various code storage and build server options. You will then learn how to test your code with a few tools and deploy your test successfully. In addition to this, you will also see how to monitor code for any anomalies and make sure that it runs as expected. Finally, you will discover how to handle logs and keep track of the issues that affect different processes. By the end of the book, you will be familiar with all the tools needed to deploy, integrate, and deliver efficiently with DevOps. Style and approach This book is primarily a technical guide to DevOps with practical examples suitable for people who like to learn by implementing concrete working code.

Design modern, rich interfaces for Java apps using JavaFX 10 About This Book ? Become a pro with the latest JavaFX 10 framework ? Create dynamic content using the animation API ? Create and customize plugins and use them efficiently in different applications Who This Book Is For If you’re a Java developer who wants to upgrade to the latest version of JavaFX to create stunning, feature-rich graphical applications, this book is for you. What You Will Learn ? Construct and customize JavaFX windows ? Manage UI elements and arrange them on the Scene ? Explore the Bindings API and use it to coordinate various UI elements ? Use FXML to design amazing FX applications ? Write and manage CSS to style your applications ? Add audio and video to your projects ? Prepare your application to be launched on the target platform In Detail JavaFX 10 is used to create media-rich client applications. This book takes you on a journey to use JavaFX 10 to build applications that display information in a high-performance, modern user interface featuring audio, video, graphics, and animation. Mastering JavaFX 10 begins by introducing you to the JavaFX API. You will understand the steps involved in setting up your development environment and build the necessary dependencies. This is followed by exploring how to work with the assets, modules, and APIs of JavaFX. This book is filled with practical examples to guide you through the major features of JavaFX 10. In addition to this, you will acquire a practical understanding of JavaFX custom animations, merging different application layers smoothly, and creating a user-friendly GUI with ease. By the end of the book, you will be able to create a complete, feature-rich Java graphical application using JavaFX. Style and approach The book adopts a practical, step-by-step approach.

Get to grips with modern software demands by learning the effective uses of Rust's powerful memory safety. About This Book ? Learn and improve the sequential performance characteristics of your software ? Understand the use of operating system processes in a high-scale concurrent system ? Learn of the various coordination methods available in the Standard library Who This Book Is For This book is aimed at software engineers with a basic understanding of Rust who want to exploit the parallel and concurrent nature of modern computing environments, safely. What You Will Learn ? Probe your programs for performance and accuracy issues ? Create your own threading and multi-processing environment in Rust ? Use coarse locks from Rust’s Standard library ? Solve common synchronization problems or avoid synchronization using atomic programming ? Build lock-free/wait-free structures in Rust and understand their implementations in the crates ecosystem ? Leverage Rust’s memory model and type system to build safety properties into your parallel programs ? Understand the new features of the Rust programming language to ease the writing of parallel programs In Detail Most programming languages can really complicate things, especially with regard to unsafe memory access. The burden on you, the programmer, lies across two domains: understanding the modern machine and your language's pain-points. This book will teach you to how to manage program performance on modern machines and build fast, memory-safe, and concurrent software in Rust. It starts with the fundamentals of Rust and discusses machine architecture concepts. You will be taken through ways to measure and improve the performance of Rust code systematically and how to write collections with confidence. You will learn about the Sync and Send traits applied to threads, and coordinate thread execution with locks, atomic primitives, data-parallelism, and more. The book will show you how to efficiently embed Rust in C++ code and explore the functionalities of various crates for multithreaded applications. It explores implementations in depth. You will know how a mutex works and build several yourself. You will master radically different approaches that exist in the ecosystem for structuring and managing high-scale systems. By the end of the book, you will feel comfortable with designing safe, consistent, parallel, and high-performance applications in Rust. Style and approach Readers will be taken through various ways to improve the performance of their Rust code.