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Podcasts
Serverless architecture is popular in the tech community due to AWS Lambda. Go is simple to learn, straightforward to work with, and easy to read for other developers; and now it's been heralded as a supported language for AWS Lambda. This book is your optimal guide to designing a Go serverless application and deploying it to Lambda.This book starts with a quick introduction to the world of serverless architecture and its benefits, and then delves into AWS Lambda using practical examples. You'll then learn how to design and build a production-ready application in Go using AWS serverless services with zero upfront infrastructure investment. The book will help you learn how to scale up serverless applications and handle distributed serverless systems in production. You will also learn how to log and test your application.Along the way, you'll also discover how to set up a CI/CD pipeline to automate the deployment process of your Lambda functions. Moreover, you'll learn how to troubleshoot and monitor your apps in near real-time with services such as AWS CloudWatch and X-ray. This book will also teach you how to secure the access with AWS Cognito.By the end of this book, you will have mastered designing, building, and deploying a Go serverless application.
Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving.The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator.By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems.
Enterprise Agility. Being Agile in a Changing World
The biggest challenge enterprises face today is dealing with fast-paced change in all spheres of business. Enterprise Agility shows how an enterprise can address this challenge head on and thrive in the dynamic environment. Avoiding the mechanistic construction of existing enterprises that focus on predictability and certainty, Enterprise Agility delivers practical advice for responding and adapting to the scale and accelerating pace of disruptive change in the business environment.Agility is a fundamental shift in thinking about how enterprises work to effectively deal with disruptive changes in the business environment. The core belief underlying agility is that enterprises are open and living systems. These living systems, also known as complex adaptive systems (CAS), are ideally suited to deal with change very effectively.Agility is to enterprises what health is to humans. There are some foundational principles that can be broadly applied, but the definition of healthy is very specific to each individual. Enterprise Agility takes a similar approach with regard to agility: it suggests foundational practices to improve the overall health of the body—culture, mindset, and leadership—and the health of its various organs: people, process, governance, structure, technology, and customers. The book also suggests a practical framework to create a plan to enhance agility.
Alok Malik, Bradford Tuckfield
Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection.
Bootstrap 4 Cookbook. Solutions to common problems faced in Responsive Web Design
Bootstrap, one of the most popular front-end frameworks, is perfectly built to design elegant, powerful, and responsive interfaces for professional-level web pages. It supports responsive design by dynamically adjusting your web page layout.Bootstrap 4 is a major update with many impressive changes that greatly enhance the end results produced by Bootstrap. This cookbook is a collection of great recipes that show you how to use all the latest features of Bootstrap to build compelling UIs.This book is using the most up-to-date version of Bootstrap 4 in all its chapters. First off, you will be shown how you can leverage the latest core features of Bootstrap 4 to create stunning web pages and responsive media. You will gradually move on to extending Bootstrap 4 with the help of plugins to build highly customized and powerful UIs.By the end of this book, you will know how to leverage, extend, and integrate bootstrap to achieve optimal results for your web projects.
Projects like Angular and React are rapidly changing how development teams build and deploy web applications to production. In this book, you’ll learn the basics you need to get up and running with React and tackle real-world projects and challenges. It includes helpful guidance on how to consider key user requirements within the development process, and also shows you how to work with advanced concepts such as state management, data-binding, routing, and the popular component markup that is JSX. As you complete the included examples, you’ll find yourself well-equipped to move onto a real-world personal or professional frontend project.
HoloLens Beginner's Guide. Join the AR revolution with HoloLens
HoloLens revolutionizes the way we work and interact with the virtual world. HoloLens brings you the amazing world of augmented reality and provides an opportunity to explore it like never before. This is the best book for developers who want to start creating interactive and intuitive augmented reality apps for the HoloLens platform.You will start with a walkthrough of the HoloLens hardware before creating your first app. Next you will be introduced to the various HoloLens sensors and find out how to program them efficiently so that they can interact with the real world seamlessly. Moving on, you will learn how to create smart animations and add video overlay that implements real-time tracking and motion-sensing abilities to your HoloLens app. Finally, you will learn how to test your app effectively.
Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured.The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate machine learning algorithms to use for your projects with the help of a facial detection project.By the end of this book, you will have developed a solid machine learning mindset, a strong hold on the powerful Go toolkit, and a sound understanding of the practical implementations of machine learning algorithms in real-world projects.