ASP.NET Core 2 High Performance. Learn the secrets of developing high performance web applications using C# and ASP.NET Core 2 on Windows, Mac, and Linux - Second Edition

James Singleton

The ASP.NET Core 2 framework is used to develop high-performance and cross-platform web applications. It is built on .NET Core 2 and includes significantly more framework APIs than version 1.This book addresses high-level performance improvement techniques. It starts by showing you how to locate and measure problems and then shows you how to solve some of the most common ones. Next, it shows you how to get started with ASP.NET Core 2 on Windows, Mac, Linux, and with Docker containers.The book illustrates what problems can occur as latency increases when deploying to a cloud infrastructure. It also shows you how to optimize C# code and choose the best data structures for the job. It covers new features in C# 6 and 7, along with parallel programming and distributed architectures.By the end of this book, you will be fixing latency issues and optimizing performance problems, but you will also know how this affects the complexity and maintenance of your application. Finally, we will explore a few highly advanced techniques for further optimization.

Machine Learning Fundamentals. Use Python and scikit-learn to get up and running with the hottest developments in machine learning

Hyatt Saleh

As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithms over real-world datasets, to discover patterns and profiles, and explore the process to solve an unsupervised machine learning problem.The focus of the book then shifts to supervised learning algorithms. You'll learn to implement different supervised algorithms and develop neural network structures using the scikit-learn package. You'll also learn how to perform coherent result analysis to improve the performance of the algorithm by tuning hyperparameters.By the end of this book, you will have gain all the skills required to start programming machine learning algorithms.

Hands-On Concurrency with Rust. Confidently build memory-safe, parallel, and efficient software in Rust

Brian L. Troutwine

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.

Security Automation with Ansible 2. Leverage Ansible 2 to automate complex security tasks like application security, network security, and malware analysis

Akash Mahajan, MADHU AKULA

Security automation is one of the most interesting skills to have nowadays. Ansible allows you to write automation procedures once and use them across your entire infrastructure. This book will teach you the best way to use Ansible for seemingly complex tasks by using the various building blocks available and creating solutions that are easy to teach others, store for later, perform version control on, and repeat.We’ll start by covering various popular modules and writing simple playbooks to showcase those modules. You’ll see how this can be applied over a variety of platforms and operating systems, whether they are Windows/Linux bare metal servers or containers on a cloud platform. Once the bare bones automation is in place, you’ll learn how to leverage tools such as Ansible Tower or even Jenkins to create scheduled repeatable processes around security patching, security hardening, compliance reports, monitoring of systems, and so on. Moving on, you’ll delve into useful security automation techniques and approaches, and learn how to extend Ansible for enhanced security. While on the way, we will tackle topics like how to manage secrets, how to manage all the playbooks that we will create and how to enable collaboration using Ansible Galaxy. In the final stretch, we’ll tackle how to extend the modules of Ansible for our use, and do all the previous tasks in a programmatic manner to get even more powerful automation frameworks and rigs.

UX Design for Mobile. Design apps that deliver impressive mobile experiences

Pablo Perea, Pau Giner

User experience (UX) design provides techniques to analyze the real needs of your users and respond to them with products that are delightful to use. This requires you to think differently compared to traditional development processes, but also to act differently. In this book, you will be introduced to a pragmatic approach to exploring and creating mobile app solutions, reducing risks and saving time during their construction. This book will show you a working process to quickly iterate product ideas with low and high fidelity prototypes, based on professional tools from different software brands. You will be able to quickly test your ideas early in the process with the most adequate prototyping approach. You will understand the pros and cons of each approach, when you should use each of them, and what you can learn in each step of the testing process. You will also explore basic testing approaches and some more advanced techniques to connect and learn from your users. Each chapter will focus on one of the general steps needed to design a successful product according to the organization goals and the user needs. To achieve this, the book will provide detailed hands-on pragmatic techniques to design innovative and easy to use products. You will learn how to test your ideas in the early steps of the design process, picking up the best ideas that truly work with your users, rethinking those that need further refinement, and discarding those that don’t work properly in tests made with real users.By the end of the book, you will learn how to start exploring and testing your design ideas, regardless the size of the design budget.

Learning AWS. Design, build, and deploy responsive applications using AWS Cloud components - Second Edition

Aurobindo Sarkar, Amit Shah

Amazon Web Services (AWS) is the most popular and widely-used cloud platform. Administering and deploying application on AWS makes the applications resilient and robust. The main focus of the book is to cover the basic concepts of cloud-based development followed by running solutions in AWS Cloud, which will help the solutions run at scale.This book not only guides you through the trade-offs and ideas behind efficient cloud applications, but is a comprehensive guide to getting the most out of AWS. In the first section, you will begin by looking at the key concepts of AWS, setting up your AWS account, and operating it. This guide also covers cloud service models, which will help you build highly scalable and secure applications on the AWS platform. We will then dive deep into concepts of cloud computing with S3 storage, RDS and EC2. Next, this book will walk you through VPC, building real-time serverless environments, and deploying serverless APIs with microservices. Finally, this book will teach you to monitor your applications, automate your infrastructure, and deploy with CloudFormation.By the end of this book, you will be well-versed with the various services that AWS provides and will be able to leverage AWS infrastructure to accelerate the development process.

Django 2 by Example. Build powerful and reliable Python web applications from scratch

Antonio Melé

If you want to learn the entire process of developing professional web applications with Django 2, then this book is for you. You will walk through the creation of four professional Django 2 projects, teaching you how to solve common problems and implement best practices.You will learn how to build a blog application, a social image bookmarking website, an online shop and an e-learning platform. The book will teach you how to enhance your applications with AJAX, create RESTful APIs and set up a production environment for your Django 2 projects. The book walks you through the creation of real-world applications, solving common problems, and implementing best practices. By the end of this book, you will have a deep understanding of Django 2 and how to build advanced web applications.

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.