Building Computer Vision Projects with OpenCV 4 and C++. Implement complex computer vision algorithms and explore deep learning and face detection

David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation.This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books:•Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá•Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi

Building Data Science Applications with FastAPI. Develop, manage, and deploy efficient machine learning applications with Python

François Voron

FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you’ll be able to create fast and reliable data science API backends using practical examples.This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you’ll cover best practices relating to testing and deployment to run a high-quality and robust application. You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you’ll see how to implement a real-time face detection system using WebSockets and a web browser as a client.By the end of this FastAPI book, you’ll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.

Building Data Streaming Applications with Apache Kafka. Design, develop and streamline applications using Apache Kafka, Storm, Heron and Spark

Chanchal Singh, Manish Kumar

Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur.This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security.By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it.

Building Data-Driven Applications with LlamaIndex. A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Andrei Gheorghiu

Discover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.

Building ERP Solutions with Microsoft Dynamics NAV. Solve business scenarios using NAV

Stefano Demiliani

Implementing Microsoft Dynamics NAV in the real world often requires you to integrate the ERP with external applications or solve complex architectural tasks in order to have a final successful project. This book will show you how to extend a Microsoft Dynamics NAV installation to the enterprise world in a practical way.The book starts with an introduction to Microsoft Dynamics NAV architecture and then moves on to advanced topics related to implementing real-world solutions based on NAV and external applications. You will learn how an enterprise distributed architecture with NAV at the core can be implemented. Through a series of real-world cases on every topic and every industry (sales, retail, manufacturing, distribution, healthcare, and so on), you’ll see step by step how to efficiently solve a technical problem. These common problems encountered in a NAV implementation will be solved using the entire technology stack that Microsoft offers.By the end of the book, you will have the knowledge to efficiently solve certain scenarios, you will know which is the best solution architecture to propose to a customer and how to implement it.

Building Google Cloud Platform Solutions. Develop scalable applications from scratch and make them globally available in almost any language

Ted Hunter, Steven Porter, Legorie Rajan PS

GCP is a cloud computing platform with a wide range of products and services that enable you to build and deploy cloud-hosted applications. This Learning Path will guide you in using GCP and designing, deploying, and managing applications on Google Cloud.You will get started by learning how to use App Engine to access Google's scalable hosting and build software that runs on this framework. With the help of Google Compute Engine, you’ll be able to host your workload on virtual machine instances. The later chapters will help you to explore ways to implement authentication and security, Cloud APIs, and command-line and deployment management. As you hone your skills, you’ll understand how to integrate your new applications with various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. Following this, the book will teach you how to streamline your workflow with tools, including Source Repositories, Container Builder, and Stackdriver. You'll also understand how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerts for your production systems. By the end of this Learning Path, you'll be well versed with GCP’s development tools and be able to develop, deploy, and manage highly scalable and reliable applications.This Learning Path includes content from the following Packt products:• Google Cloud Platform for Developers Ted Hunter and Steven Porter• Google Cloud Platform Cookbook by Legorie Rajan PS

Building Hybrid Clouds with Azure Stack. Implementing on-premises Azure infrastructure

Markus Klein, Susan Roesner

Azure Stack is all about creating fewer gaps between on-premise and public cloud application deployment. Azure Stack is the logical progression of Microsoft Cloud Services to create a true hybrid cloud-ready application.This book provides an introduction to Azure Stack and the cloud-first approach. Starting with an introduction to the architecture of Azure Stack, the book will help you plan and deploy your Azure Stack. Next, you will learn about the network and storage options in Azure Stack and you'll create your own private cloud solution. Finally, you will understand how to integrate public cloud using the third-party resource provider. After reading the book, you will have a good understanding of the end-to-end process of designing, offering, and supporting cloud solutions for enterprises or service providers.

Building Industrial Digital Twins. Design, develop, and deploy digital twin solutions for real-world industries using Azure Digital Twins

Shyam Varan Nath, Pieter van Schalkwyk, Dan Isaacs

Digital twin technology enables organizations to create digital representations of physical entities such as assets, systems, and processes throughout their life cycle. It improves asset performance, utilization, and safe operations and reduces manufacturing, operational, and maintenance costs.The book begins by introducing you to the concept of digital twins and sets you on a path to develop a digital twin strategy to positively influence business outcomes in your organization. You'll understand how digital twins relate to physical assets, processes, and technology and learn about the prerequisite conditions for the right platform, scale, and use case of your digital twins. You'll then get hands-on with Microsoft's Azure Digital Twins platform for your digital twin development and deployment. The book equips you with the knowledge to evaluate enterprise and specialty platforms, including the cloud and industrial IoT required to set up your digital twin prototype. Once you've built your prototype, you'll be able to test and validate it relative to the intended purpose of the twin through pilot deployment, full deployment, and value tracking techniques.By the end of this book, you'll have developed the skills to build and deploy your digital twin prototype, or minimum viable twin, to demonstrate, assess, and monitor your asset at specific stages in the asset life cycle.