Minimal CMake. Learn the best bits of CMake to create and share your own libraries and applications

Tom Hulton-Harrop

Minimal CMake guides you through creating a CMake project one step at a time. The book utilizes the author's unique expertise in game and engine development to craft compelling examples of how CMake can be used to build complex software. The chapters introduce concepts gradually, each one building on the last. Throughout the course of the book, you will progress from a simple console application all the way through to a full windowed app.The book will help you build a strong foundation in CMake that will translate to future projects. You'll learn how to integrate existing software libraries to enhance your app's functionality, how to build reusable libraries to share with others, and how to manage developing for multiple platforms simultaneously, including macOS, Windows, and Linux. You'll also find out how CMake facilitates testing and how to package your application ready for distribution.The book aims to not overwhelm you with everything there is to know about CMake. Instead, it focuses on the most relevant and important parts that will help you become productive quickly.By the end of this book, you will be a confident CMake user and will have gained the skills and experience to build and share your own libraries and applications.

Mastering AWS CloudFormation. Plan, develop, and deploy your cloud infrastructure effectively using AWS CloudFormation

Karen Tovmasyan

DevOps and the cloud revolution have forced software engineers and operations teams to rethink how to manage infrastructures. With this AWS book, you'll understand how you can use Infrastructure as Code (IaC) to simplify IT operations and manage the modern cloud infrastructure effectively with AWS CloudFormation.This comprehensive guide will help you explore AWS CloudFormation from template structures through to developing complex and reusable infrastructure stacks. You'll then delve into validating templates, deploying stacks, and handling deployment failures. The book will also show you how to leverage AWS CodeBuild and CodePipeline to automate resource delivery and apply continuous integration and continuous delivery (CI/CD) practices to the stack. As you advance, you'll learn how to generate templates on the fly using macros and create resources outside AWS with custom resources. Finally, you'll improve the way you manage the modern cloud in AWS by extending CloudFormation using AWS serverless application model (SAM) and AWS cloud development kit (CDK).By the end of this book, you'll have mastered all the major AWS CloudFormation concepts and be able to simplify infrastructure management.

WordPress Search Engine Optimization. A complete guide to dominating search engines with your WordPress site

Michael David, Michael David

WordPress is a powerful platform for creating feature-rich and attractive websites but, with a little extra tweaking and effort, your WordPress site can dominate search engines and bring thousands of new customers to your business.WordPress Search Engine Optimization will show you the secrets that professional SEO companies use to take websites to the top of search results. You'll take your WordPress site to the next level; you'll brush aside even the stiffest competition with the advanced tutorials in this book.

Visual Studio 2013 and .NET 4.5 Expert Cookbook. Over 30 recipes to successfully mix the powerful capabilities of Visual Studio 2013 with .NET 4.5

Abhishek Sur, Abhishek Sur

Active Machine Learning with Python. Refine and elevate data quality over quantity with active learning

Margaux Masson-Forsythe

Building accurate machine learning models requires quality data—lots of it. However, for most teams, assembling massive datasets is time-consuming, expensive, or downright impossible. Led by Margaux Masson-Forsythe, a seasoned ML engineer and advocate for surgical data science and climate AI advancements, this hands-on guide to active machine learning demonstrates how to train robust models with just a fraction of the data using Python's powerful active learning tools.You’ll master the fundamental techniques of active learning, such as membership query synthesis, stream-based sampling, and pool-based sampling and gain insights for designing and implementing active learning algorithms with query strategy and Human-in-the-Loop frameworks. Exploring various active machine learning techniques, you’ll learn how to enhance the performance of computer vision models like image classification, object detection, and semantic segmentation and delve into a machine AL method for selecting the most informative frames for labeling large videos, addressing duplicated data. You’ll also assess the effectiveness and efficiency of active machine learning systems through performance evaluation.By the end of the book, you’ll be able to enhance your active learning projects by leveraging Python libraries, frameworks, and commonly used tools.

R for Data Science Cookbook. Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques

Yu-Wei, Chiu (David Chiu)

This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently.The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the “dplyr” and “data.table” packages to efficiently process larger data structures. We also focus on “ggplot2” and show you how to create advanced figures for data exploration.In addition, you will learn how to build an interactive report using the “ggvis” package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction.By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis.

Yii Project Blueprints. From conception to production, learn how to develop real-world applications with the Yii framework

Charles R. Portwood ll

Hands-On Simulation Modeling with Python. Develop simulation models for improved efficiency and precision in the decision-making process - Second Edition

Giuseppe Ciaburro

Simulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it. The ability to analyze the model as it runs sets simulation modelling apart from other methods used in conventional analyses. This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python. The book begins by helping you get familiarized with the fundamental concepts of simulation modelling, that’ll enable you to understand the various methods and techniques needed to explore complex topics. Data scientists working with simulation models will be able to put their knowledge to work with this practical guide. As you advance, you’ll dive deep into numerical simulation algorithms, including an overview of relevant applications, with the help of real-world use cases and practical examples. You'll also find out how to use Python to develop simulation models and how to use several Python packages. Finally, you’ll get to grips with various numerical simulation algorithms and concepts, such as Markov Decision Processes, Monte Carlo methods, and bootstrapping techniques.By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.