Learning Julia. Build high-performance applications for scientific computing

Anshul Joshi, Rahul Lakhanpal

Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all.This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set.The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on.By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain.

Neural Network Programming with Tensorflow. Unleash the power of TensorFlow to train efficient neural networks

Manpreet Singh Ghotra, Rajdeep Dua

If you're aware of the buzz surrounding the terms such as machine learning, artificial intelligence, or deep learning, you might know what neural networks are. Ever wondered how they help in solving complex computational problem efficiently, or how to train efficient neural networks? This book will teach you just that.You will start by getting a quick overview of the popular TensorFlow library and how it is used to train different neural networks. You will get a thorough understanding of the fundamentals and basic math for neural networks and why TensorFlow is a popular choice Then, you will proceed to implement a simple feed forward neural network. Next you will master optimization techniques and algorithms for neural networks using TensorFlow. Further, you will learn to implement some more complex types of neural networks such as convolutional neural networks, recurrent neural networks, and Deep Belief Networks. In the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn the applications of autoencoders.By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how they map to the appropriate TensorFlow constructs.

Ensemble Machine Learning Cookbook. Over 35 practical recipes to explore ensemble machine learning techniques using Python

Dipayan Sarkar, Vijayalakshmi Natarajan

Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking.The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you’ll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You’ll also be able to implement models such as fraud detection, text categorization, and sentiment analysis.By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes.

AWS: Security Best Practices on AWS. Learn to secure your data, servers, and applications with AWS

Albert Anthony

With organizations moving their workloads, applications, and infrastructure to the cloud at an unprecedented pace, security of all these resources has been a paradigm shift for all those who are responsible for security; experts, novices, and apprentices alike.This book focuses on using native AWS security features and managed AWS services to help you achieve continuous security. Starting with an introduction to Virtual Private Cloud (VPC) to secure your AWS VPC, you will quickly explore various components that make up VPC such as subnets, security groups, various gateways, and many more.You will also learn to protect data in the AWS platform for various AWS services by encrypting and decrypting data in AWS. You will also learn to secure web and mobile applications in AWS cloud.This book is ideal for all IT professionals, system administrators, security analysts, solution architects, and chief information security officers who are responsible for securing workloads in AWS for their organizations.This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. This book is repurposed for this specific learning experience from material from Packt's Mastering AWS Security, written by Albert Anthony.

Mastering Qlik Sense. Expert techniques on self-service data analytics to create enterprise ready Business Intelligence solutions

Martin Mahler, Juan Ignacio Vitantonio

Qlik Sense is a powerful, self-servicing Business Intelligence tool for data discovery, analytics and visualization. It allows you to create personalized Business Intelligence solutions from raw data and get actionable insights from it.This book is your one-stop guide to mastering Qlik Sense, catering to all your organizational BI needs. You'll see how you can seamlessly navigate through tons of data from multiple sources and take advantage of the various APIs available in Qlik and its components for guided analytics. You'll also learn how to embed visualizations into your existing BI solutions and extend the capabilities of Qlik Sense to create new visualizations and dashboards that work across all platforms. We also cover other advanced concepts such as porting your Qlik View applications to Qlik Sense,and working with Qlik Cloud. Finally, you'll implement enterprise-wide security and access control for resources and data sources through practical examples.With the knowledge gained from this book, you'll have become the go-to expert in your organization when it comes to designing BI solutions using Qlik Sense.

Mastering Distributed Tracing. Analyzing performance in microservices and complex systems

Yuri Shkuro

Mastering Distributed Tracing will equip you to operate and enhance your own tracing infrastructure. Through practical exercises and code examples, you will learn how end-to-end tracing can be used as a powerful application performance management and comprehension tool. The rise of Internet-scale companies, like Google and Amazon, ushered in a new era of distributed systems operating on thousands of nodes across multiple data centers. Microservices increased that complexity, often exponentially. It is harder to debug these systems, track down failures, detect bottlenecks, or even simply understand what is going on. Distributed tracing focuses on solving these problems for complex distributed systems. Today, tracing standards have developed and we have much faster systems, making instrumentation less intrusive and data more valuable.Yuri Shkuro, the creator of Jaeger, a popular open-source distributed tracing system, delivers end-to-end coverage of the field in Mastering Distributed Tracing. Review the history and theoretical foundations of tracing; solve the data gathering problem through code instrumentation, with open standards like OpenTracing, W3C Trace Context, and OpenCensus; and discuss the benefits and applications of a distributed tracing infrastructure for understanding, and profiling, complex systems.

Mastering Linux Kernel Development. A kernel developer's reference manual

CH Raghav Maruthi

Mastering Linux Kernel Development looks at the Linux kernel, its internal arrangement and design, and various core subsystems, helping you to gain significant understanding of this open source marvel. You will look at how the Linux kernel, which possesses a kind of collective intelligence thanks to its scores of contributors, remains so elegant owing to its great design.This book also looks at all the key kernel code, core data structures, functions, and macros, giving you a comprehensive foundation of the implementation details of the kernel’s core services and mechanisms. You will also look at the Linux kernel as well-designed software, which gives us insights into software design in general that are easily scalable yet fundamentally strong and safe.By the end of this book, you will have considerable understanding of and appreciation for the Linux kernel.

Mastering Predictive Analytics with R. Machine learning techniques for advanced models - Second Edition

James D. Miller, Rui Miguel Forte

R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks.By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R.

Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems

Matthew Lamons, Rahul Kumar, Abhishek Nagaraja

Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You’ll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.Similarly, you’ll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you’ll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects.By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way

R Programming Fundamentals. Deal with data using various modeling techniques

Kaelen Medeiros

R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. You’ll start by understanding how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops.Once you have grasped the basics, you’ll move on to studying data visualization and graphics. You’ll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you’ll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values.By the end of this book, you’ll have completed an entire data science project of your own for your portfolio or blog.

Cloud Native Python. Build and deploy resilent applications on the cloud using microservices, AWS, Azure and more

Manish Sethi

Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you’ve deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform

Mastering Blockchain. Deeper insights into decentralization, cryptography, Bitcoin, and popular Blockchain frameworks

Imran Bashir

Blockchain is a distributed database that enables permanent, transparent, and secure storage of data. The blockchain technology is the backbone of cryptocurrency – in fact, it’s the shared public ledger upon which the entire Bitcoin network relies – and it’s gaining popularity with people who work in finance, government, and the arts.Blockhchain technology uses cryptography to keep data secure. This book gives a detailed description of this leading technology and its implementation in the real world.This book begins with the technical foundations of blockchain, teaching you the fundamentals of cryptography and how it keeps data secure. You will learn about the mechanisms behind cryptocurrencies and how to develop applications using Ethereum, a decentralized virtual machine. You will explore different blockchain solutions and get an exclusive preview into Hyperledger, an upcoming blockchain solution from IBM and the Linux Foundation. You will also be shown how to implement blockchain beyond currencies, scability with blockchain, and the future scope of this fascinating and powerful technology.

Windows Server 2016 Hyper-V Cookbook. Save time and resources by getting to know the best practices and intelligence from industry experts - Second Edition

Charbel Nemnom, Patrick Lownds, Leandro Carvalho

Hyper-V 2016 is full of new features and updates. The second of our best-selling Hyper-V books, the Windows Server 2016 Hyper-V Cookbook has it all covered. Brimming with expert solutions and techniques, you?ll have everything you need to master virtualization and Hyper-V Manager. This Hyper-V book is designed to help advanced-level administrators benefit fully from the new Windows Server. With over 80 hands-on recipes, the Hyper-V Cookbook gives you tips, tricks and best practices to deploy, maintain and upgrade your virtual machines.

Learn Swift by Building Applications. Explore Swift programming through iOS app development

Emil Atanasov, Emil Atanasov

Swift Language is now more powerful than ever; it has introduced new ways to solve old problems and has gone on to become one of the fastest growing popular languages. It is now a de-facto choice for iOS developers and it powers most of the newly released and popular apps. This practical guide will help you to begin your journey with Swift programming through learning how to build iOS apps.You will learn all about basic variables, if clauses, functions, loops, and other core concepts; then structures, classes, and inheritance will be discussed. Next, you’ll dive into developing a weather app that consumes data from the internet and presents information to the user. The final project is more complex, involving creating an Instagram like app that integrates different external libraries. The app also uses CocoaPods as its package dependency manager, to give you a cutting-edge tool to add to your skillset. By the end of the book, you will have learned how to model real-world apps in Swift.

Getting Started with Angular. Click here to enter text. - Second Edition

Minko Gechev

Want to build quick and robust web applications with Angular? This book is the quickest way to get to grips with Angular and take advantage of all its new features.

The Modern C++ Challenge. Become an expert programmer by solving real-world problems

Marius Bancila, Scott Meyers

C++ is one of the most widely-used programming languages and has applications in a variety of fields, such as gaming, GUI programming, and operating systems, to name a few. Through the years, C++ has evolved into (and remains) one of the top choices for software developers worldwide. This book will show you some notable C++ features and how to implement them to meet your application needs. Each problem is unique and doesn't just test your knowledge of the language; it tests your ability to think out of the box and come up with the best solutions. With varying levels of difficulty, you'll be faced with a wide variety of challenges. And in case you're stumped, you don't have to worry: we've got the best solutions to the problems in the book. So are you up for the challenge?