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Building Microservices with Spring
Building Microservices with Spring

Getting Started with Spring Microservices begins with an overview of the Spring Framework 5.0, its design patterns, and its guidelines that enable you to implement responsive microservices at scale. You will learn how to use GoF patterns in application design. You will understand the dependency injection pattern, which is the main principle behind the decoupling process of the Spring Framework and makes it easier to manage your code. Then, you will learn how to use proxy patterns in aspect-oriented programming and remoting. Moving on, you will understand the JDBC template patterns and their use in abstracting database access. After understanding the basics, you will move on to more advanced topics, such as reactive streams and concurrency. Written to the latest specifications of Spring that focuses on Reactive Programming, the Learning Path teaches you how to build modern, internet-scale Java applications in no time. Next, you will understand how Spring Boot is used to deploying ...
Learn Robotics with Raspberry Pi
Learn Robotics with Raspberry Pi

Learn Robotics with Raspberry Pi will take you from inexperienced maker to robot builder. You'll start off building a two-wheeled robot powered by a Raspberry Pi minicomputer and then program it using Python, the world's most popular programming language. Gradually, you'll improve your robot by adding increasingly advanced functionality until it can follow lines, avoid obstacles, and even recognize objects of a certain size and color using computer vision. Learn how to: Control your robot remotely using only a Wii remote; Teach your robot to use sensors to avoid obstacles; Program your robot to follow a line autonomously; Customize your robot with LEDs and speakers to make it light up and play sounds; See what your robot sees with a Pi Camera. As you work through the book, you'll learn fundamental electronics skills like how to wire up parts, use resistors and regulators, and determine how much power your robot needs. By the end, you'll have learned the basics of coding in Python ...
3D Industrial Printing with Polymers
3D Industrial Printing with Polymers

3D industrial printing has become mainstream in manufacturing. This unique book is the first to focus on polymers as the printing material. The scientific literature with respect to 3D printing is collated in this monograph. The book opens with a chapter on foundational issues such and presents a broad overview of 3D printing procedures and the materials used therein. In particular, the methods of 3d printing are discussed and the polymers and composites used for 3d printing are detailed. The book details the main fields of applications areas which include electric and magnetic uses, medical applications, and pharmaceutical applications. Electric and magnetic uses include electronic materials, actuators, piezoelectric materials, antennas, batteries and fuel cells. Medical applications are organ manufacturing, bone repair materials, drug-eluting coronary stents, and dental applications. The pharmaceutical applications are composite tablets, transdermal drug delivery, and patient-s ...
Exploring BeagleBone, 2nd Edition
Exploring BeagleBone, 2nd Edition

Exploring BeagleBone is a hands-on guide to bringing gadgets, gizmos, and robots to life using the popular BeagleBone embedded Linux platform. Comprehensive content and deep detail provide more than just a BeagleBone instruction manual-you'll also learn the underlying engineering techniques that will allow you to create your own projects. The book begins with a foundational primer on essential skills, and then gradually moves into communication, control, and advanced applications using C/C++, allowing you to learn at your own pace. In addition, the book's companion website features instructional videos, source code, discussion forums, and more, to ensure that you have everything you need. The BeagleBone's small size, high performance, low cost, and extreme adaptability have made it a favorite development platform, and the Linux software base allows for complex yet flexible functionality. The BeagleBone has applications in smart buildings, robot control, environmental sensing, to nam ...
Natural Language Processing Recipes
Natural Language Processing Recipes

Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis. Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You'll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing. By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real w ...
Blazor Revealed
Blazor Revealed

Build web applications in Microsoft .NET that run in any modern browser, helping you to transfer your .NET experience and skills to a new environment and build browser-based applications using a robust and type-safe language and runtime. Developing a web site with rich client-side behavior means most developers need to learn a transpiled language like JavaScript or TypeScript. But today you can also develop rich browser applications using the .NET runtime and C# using Blazor. With Blazor you can use all that experience you have amassed over the years, and can use thousands of already existing libraries, right in the browser. Blazor Revealed will allow you to create a rich web site experience in no time. You will learn how to build user interfaces, and present data to a user for display and modification, capturing the user's changes via data binding. The book shows you how to access a rich library of .NET functionality such as a component model for building a composable user interfac ...
Python: Beginner's Guide to Artificial Intelligence
Python: Beginner's Guide to Artificial Intelligence

This Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. You'll find a new balance of classical ideas and modern insights into machine learning. You will learn to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open-source Python libraries. Throughout the Learning Path, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and Autoencoders. Discover how to attain deep learning programming on GPU in a distributed way. By the end of this Learning Path, you know the fundamentals of AI and have worked through a n ...
Tableau 10 Complete Reference
Tableau 10 Complete Reference

Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You'll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also cov ...
Deep Learning with PyTorch Quick Start Guide
Deep Learning with PyTorch Quick Start Guide

PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. ...
Apache Spark 2: Data Processing and Real-Time Analytics
Apache Spark 2: Data Processing and Real-Time Analytics

Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. ...
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