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

ASP.NET Core MVC 2.0 Cookbook. Effective ways to build modern, interactive web applications with ASP.NET Core MVC 2.0

Jason De Oliveira, Engin Polat, Stephane Belkheraz

The ASP.NET Core 2.0 Framework has been designed to meet all the needs of today’s web developers. It provides better control, support for test-driven development, and cleaner code. Moreover, it’s lightweight and allows you to run apps on Windows, OSX and Linux, making it the most popular web framework with modern day developers.This book takes a unique approach to web development, using real-world examples to guide you through problems with ASP.NET Core 2.0 web applications. It covers Visual Studio 2017- and ASP.NET Core 2.0-specifc changes and provides general MVC development recipes. It explores setting up .NET Core, Visual Studio 2017, Node.js modules, and NuGet. Next, it shows you how to work with Inversion of Control data pattern and caching. We explore everyday ASP.NET Core MVC 2.0 patterns and go beyond it into troubleshooting. Finally, we lead you through migrating, hosting, and deploying your code.By the end of the book, you’ll not only have explored every aspect of ASP.NET Core MVC 2.0, you’ll also have a reference you can keep coming back to whenever you need to get the job done.

Hands-On Deep Learning with Apache Spark. Build and deploy distributed deep learning applications on Apache Spark

Guglielmo Iozzia

Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark.The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark.As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models.By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases.

Modern R Programming Cookbook. Recipes to simplify your statistical applications

Jaynal Abedin

R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.

Enterprise Cloud Security and Governance. Efficiently set data protection and privacy principles

Zeal Vora

Modern day businesses and enterprises are moving to the Cloud, to improve efficiency and speed, achieve flexibility and cost effectiveness, and for on-demand Cloud services. However, enterprise Cloud security remains a major concern because migrating to the public Cloud requires transferring some control over organizational assets to the Cloud provider. There are chances these assets can be mismanaged and therefore, as a Cloud security professional, you need to be armed with techniques to help businesses minimize the risks and misuse of business data.The book starts with the basics of Cloud security and offers an understanding of various policies, governance, and compliance challenges in Cloud. This helps you build a strong foundation before you dive deep into understanding what it takes to design a secured network infrastructure and a well-architected application using various security services in the Cloud environment.Automating security tasks, such as Server Hardening with Ansible, and other automation services, such as Monit, will monitor other security daemons and take the necessary action in case these security daemons are stopped maliciously. In short, this book has everything you need to secure your Cloud environment with. It is your ticket to obtain industry-adopted best practices for developing a secure, highly available, and fault-tolerant architecture for organizations.

Chef Cookbook. Achieve powerful IT infrastructure management and automation - Third Edition

Matthias Marschall

Chef is a configuration management tool that lets you automate your more cumbersome IT infrastructure processes and control a large network of computers (and virtual machines) from one master server. This book will help you solve everyday problems with your IT infrastructure with Chef. It will start with recipes that show you how to effectively manage your infrastructure and solve problems with users, applications, and automation. You will then come across a new testing framework, InSpec, to test any node in your infrastructure.Further on, you will learn to customize plugins and write cross-platform cookbooks depending on the platform. You will also install packages from a third-party repository and learn how to manage users and applications. Toward the end, you will build high-availability services and explore what Habitat is and how you can implement it.

Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics

Rich Collier, Bahaaldine Azarmi

Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data.As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure.By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly.

Practical Data Wrangling. Expert techniques for transforming your raw data into a valuable source for analytics

Allan Visochek

Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them.You’ll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You’ll work with different data structures and acquire and parse data from various locations. You’ll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases.The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the end of the book, you’ll have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way.