Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python. Key Features * Create your own Pi-Rover or Pi-Hexipod robots * Develop practical applications in Python using Raspberry Pi * Build your own Jarvis, a highly advanced computerized AI Book Description This Learning Path takes you on a journey in the world of robotics and teaches you all that you can achieve with Raspberry Pi and Python. It teaches you to harness the power of Python with the Raspberry Pi 3 and the Raspberry Pi zero to build superlative automation systems that can transform your business. You will learn to create text classifiers, predict sentiment in words, and develop applications with the Tkinter library. Things will get more interesting when you build a human face detection and recognition system and a home automation system in Python, where different appliances are controlled using the Raspberry Pi. With such diverse robotics projects, you'll grasp the basics of robotics and its functions, and understand the integration of robotics with the IoT environment. By the end of this Learning Path, you will have covered everything from configuring a robotic controller, to creating a self-driven robotic vehicle using Python. * Raspberry Pi 3 Cookbook for Python Programmers - Third Edition by Tim Cox, Dr. Steven Lawrence Fernandes * Python Programming with Raspberry Pi by Sai Yamanoor, Srihari Yamanoor * Python Robotics Projects by Prof. Diwakar Vaish What you will learn * Build text classifiers and predict sentiment in words with the Tkinter library * Develop human face detection and recognition systems * Create a neural network module for optical character recognition * Build a mobile robot using the Raspberry Pi as a controller * Understand how to interface sensors, actuators, and LED displays work * Apply machine learning techniques to your models * Interface your robots with Bluetooth Who this book is for This Learning Path is specially designed for Python developers who want to take their skills to the next level by creating robots that can enhance people’s lives. Familiarity with Python and electronics will aid understanding the concepts in this Learning Path.

Get up to speed with creational, structural, behavioral and concurrent patterns in Delphi to write clear, concise and effective code Key Features * Delve into the core patterns and components of Delphi in order to master your application's design * Brush up on tricks, techniques, and best practices to solve common design and architectural challenges * Choose the right patterns to improve your program’s efficiency and productivity Book Description Design patterns have proven to be the go-to solution for many common programming scenarios. This book focuses on design patterns applied to the Delphi language. The book will provide you with insights into the language and its capabilities of a runtime library. You'll start by exploring a variety of design patterns and understanding them through real-world examples. This will entail a short explanation of the concept of design patterns and the original set of the 'Gang of Four' patterns, which will help you in structuring your designs efficiently. Next, you'll cover the most important 'anti-patterns' (essentially bad software development practices) to aid you in steering clear of problems during programming. You'll then learn about the eight most important patterns for each creational, structural, and behavioral type. After this, you'll be introduced to the concept of 'concurrency' patterns, which are design patterns specifically related to multithreading and parallel computation. These will enable you to develop and improve an interface between items and harmonize shared memories within threads. Toward the concluding chapters, you'll explore design patterns specific to program design and other categories of patterns that do not fall under the 'design' umbrella. By the end of this book, you'll be able to address common design problems encountered while developing applications and feel confident while building scalable projects. What you will learn * Gain insights into the concept of design patterns * Study modern programming techniques with Delphi * Keep up to date with the latest additions and program design techniques in Delphi * Get to grips with various modern multithreading approaches * Discover creational, structural, behavioral, and concurrent patterns * Determine how to break a design problem down into its component parts Who this book is for Hands-On Design Patterns with Delphi is aimed at beginner-level Delphi developers who want to build scalable and robust applications. Basic knowledge of Delphi is a must.

Unreal Engine 4 for virtual reality game design, development, User Experience design techniques and Blueprint programming to create virtual reality gameplay for HTC Vive, Oculus Rift, PSVR, and Windows Mixed Reality headsets. Key Features * Build VR games from scratch with the power of Unreal Engine 4 * Learn User Experience design practices to take your VR game to the next level * Understand the best practices to creating art for games on HTC Vive, Oculus Rift, and PSVR Book Description With the ability to put players directly in the game, virtual reality gives users the chance to experience digital worlds directly. Nevertheless, many designers are unsure where to start when working with this amazing technology. With this book, you will learn user experience design processes and create immersive gameplay experiences designed for entertainment and player comfort. Using the power of Unreal Engine 4’s Blueprint visual scripting language, you will build player interaction and locomotion systems from scratch and use these flexible systems to create a sample game, as well as develop functional 2D and 3D user interfaces for players to interact with. And also learn the best practices for creating game art for virtual reality. Finally, you will learn how to test your application with your target audience and finalize your game for distribution. By the end of this book, you will have the knowledge to be able to make the leap from traditional game development to creating immersive virtual reality experiences using Unreal Engine 4. What you will learn * Understand how to get started with VR development in Unreal Engine 4 * Design and create interaction and locomotion systems from scratch * Plan and program a sample game for VR * Understand how VR affects user experience and user interfaces * Discuss what is needed to create optimized art for VR * Test your game with users and prepare for distribution Who this book is for The audience for this book is intermediate or advanced users of Unreal Engine 4 but who have not begun working with VR technology. These users are familiar with the game engine and have an interest in VR technology. They are just beginning to explore the VR features that the game engine has to offer.

Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features * Exploit the power of Python to explore the world of data mining and data analytics * Discover machine learning algorithms to solve complex challenges faced by data scientists today * Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you’re interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You’ll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you’ll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you’ll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn * Understand the important concepts in machine learning and data science * Use Python to explore the world of data mining and analytics * Scale up model training using varied data complexities with Apache Spark * Delve deep into text and NLP using Python libraries such NLTK and gensim * Select and build an ML model and evaluate and optimize its performance * Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you’re a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial although not necessary.

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key Features * Build state-of-the-art algorithms that can solve your business' problems * Learn how to find hidden patterns in your data * Revise key concepts with hands-on exercises using real-world datasets Book Description 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. What you will learn * Implement clustering methods such as k-means, agglomerative, and divisive * Write code in R to analyze market segmentation and consumer behavior * Estimate distribution and probabilities of different outcomes * Implement dimension reduction using principal component analysis * Apply anomaly detection methods to identify fraud * Design algorithms with R and learn how to edit or improve code Who this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.

Create powerful data visualizations and unlock intelligent business insights with Tableau Key Features * Explore all the latest Tableau 2019 features and redefine business analytics for your organization * Create impressive data visualizations and interactive dashboards to get insights from your data * Learn effective data storytelling to transform how your business leverages data and makes decisions Book Description Tableau is the gold standard of business intelligence and visual analytics tools in every industry. It enables rapid data visualization and interpretation with charts, graphs, dashboards, and much more. Updated with the latest features of Tableau, this book takes you from the foundations of the Tableau 2019 paradigm through to advanced topics. This third edition of the bestselling guide by Tableau Zen Master, Milligan, will help you come to grips with updated features, such as set actions and transparent views. Beginning with installation, you'll create your first visualizations with Tableau and then explore practical examples and advanced techniques. You'll create bar charts, tree maps, scatterplots, time series, and a variety of other visualizations. Next, you'll discover techniques to overcome challenges presented by data structure and quality and engage in effective data storytelling and decision making with business critical information. Finally, you'll be introduced to Tableau Prep, and learn how to use it to integrate and shape data for analysis. By the end of this book, you will be equipped to leverage the powerful features of Tableau 2019 for decision making. What you will learn * Develop stunning visualizations that explain complexity with clarity * Explore the exciting new features of Tableau Desktop and Tableau Prep * Connect to various data sources to bring all your data together * Uncover techniques to prep and structure your data for easy analysis * Create and use calculations to solve problems and enrich analytics * Master advanced topics such as sets, LOD calcs, and much more * Enable smart decisions with clustering, distribution, and forecasting * Share your data stories to build a culture of trust and action Who this book is for This Tableau book is for anyone who wants to understand data. If you’re new to Tableau, don’t worry. This book builds on the foundations to help you understand how Tableau really works and then builds on that knowledge with practical examples before moving on to advanced techniques. Working experience with databases will be useful but is not necessary to get the most out of this book.

Build cost-effective and robust cloud solutions with Google Cloud Platform (GCP) using these simple and practical recipes Key Features * Explore the various service offerings of the GCP * Host a Python application on Google Compute Engine * Securely maintain application states with Cloud Storage, Datastore, and Bigtable Book Description 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 What you will learn * Host an application using Google Cloud Functions * Migrate a MySQL database to Cloud Spanner * Configure a network for a highly available application on GCP * Learn simple image processing using Storage and Cloud Functions * Automate security checks using Policy Scanner * Deploy and run services on App Engine and Container Engine * Minimize downtime and mitigate issues with Stackdriver Monitoring and Debugger * Integrate with big data solutions, including BigQuery, Dataflow, and Pub/Sub Who this book is for This Learning Path is for IT professionals, engineers, and developers who want to implement Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this Learning Path useful. Basic understanding of GCP and its services is a must.

Choose the smarter way to learn about containerizing your applications and running them in production. Key Features * Deploy and manage highly scalable, containerized applications with Kubernetes * Build high-availability Kubernetes clusters * Secure your applications via encapsulation, networks, and secrets Book Description Kubernetes is an open source orchestration platform for managing containers in a cluster environment. This Learning Path introduces you to the world of containerization, in addition to providing you with an overview of Docker fundamentals. As you progress, you will be able to understand how Kubernetes works with containers. Starting with creating Kubernetes clusters and running applications with proper authentication and authorization, you'll learn how to create high-availability Kubernetes clusters on Amazon Web Services (AWS), and also learn how to use kubeconfig to manage different clusters. Whether it is learning about Docker containers and Docker Compose, or building a continuous delivery pipeline for your application, this Learning Path will equip you with all the right tools and techniques to get started with containerization. By the end of this Learning Path, you will have gained hands-on experience of working with Docker containers and orchestrators, including SwarmKit and Kubernetes. This Learning Path includes content from the following Packt products: * Kubernetes Cookbook - Second Edition by Hideto Saito, Hui-Chuan Chloe Lee, and Ke-Jou Carol Hsu * Learn Docker - Fundamentals of Docker 18.x by Gabriel N. Schenker What you will learn * Build your own container cluster * Run a highly distributed application with Docker Swarm or Kubernetes * Update or rollback a distributed application with zero downtime * Containerize your traditional or microservice-based application * Build a continuous delivery pipeline for your application * Track metrics and logs for every container in your cluster * Implement container orchestration to streamline deploying and managing applications Who this book is for This beginner-level Learning Path is designed for system administrators, operations engineers, DevOps engineers, and developers who want to get started with Docker and Kubernetes. Although no prior experience with Docker is required, basic knowledge of Kubernetes and containers will be helpful.

Learn to distribute network traffic, optimize application delivery, and defend network-level threats. Key Features * Quickly get up and running with Azure networking solutions * Level-up your cloud networking skills by planning, implementing, configuring, and securing your infrastructure network with Azure * Leverage Azure networking services to provide applications highly available and fault tolerant environment Book Description Microsoft provides organizations with an effective way of managing their network with Azure's networking services. No matter the size of your organization, Azure provides a way to highly reliable performance and secure connectivity with its networking services. The book starts with an introduction to the Azure networking like creating Azure virtual networks, designing address spaces and subnets. Then you will learn to create and manage network security groups, application security groups, and IP addresses in Azure. Gradually, we move on to various aspects like S2S, P2S, and Vnet2Vnet connections, DNS and routing, load balancers and traffic manager. This book will cover every aspect and function required to deliver practical recipes to help readers learn from basic cloud networking practices to planning, implementing, and securing their infrastructure network with Azure. Readers will not only be able to upscale their current environment but will also learn to monitor, diagnose, and ensure secure connectivity. After learning to deliver a robust environment readers will also gain meaningful insights from recipes on best practices. By the end of this book, readers will gain hands-on experience in providing cost-effective solutions that benefit organizations. What you will learn * Learn to create Azure networking services * Understand how to create and work on hybrid connections * Configure and manage Azure network services * Learn ways to design high availability network solutions in Azure * Discover how to monitor and troubleshoot Azure network resources * Learn different methods of connecting local networks to Azure virtual networks Who this book is for This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on the Azure cloud. Some prior understanding of Microsoft Azure will be a plus point.

Use self-driven data centers to reduce management complexity by deploying Infrastructure as Code to gain value from investments. Key Features * Add smart capabilities in VMware Workspace ONE to deliver customer insights and improve overall security * Optimize your HPC and big data infrastructure with the help of machine learning * Automate your VMware data center operations with machine learning Book Description This book presents an introductory perspective on how machine learning plays an important role in a VMware environment. It offers a basic understanding of how to leverage machine learning primitives, along with a deeper look into integration with the VMware tools used for automation today. This book begins by highlighting how VMware addresses business issues related to its workforce, customers, and partners with emerging technologies such as machine learning to create new, intelligence-driven, end user experiences. You will learn how to apply machine learning techniques incorporated in VMware solutions for data center operations. You will go through management toolsets with a focus on machine learning techniques. At the end of the book, you will learn how the new vSphere Scale-Out edition can be used to ensure that HPC, big data performance, and other requirements can be met (either through development or by fine-tuning guidelines) with mainstream products. What you will learn * Orchestrate on-demand deployments based on defined policies * Automate away common problems and make life easier by reducing errors * Deliver services to end users rather than to virtual machines * Reduce rework in a multi-layered scalable manner in any cloud * Explore the centralized life cycle management of hybrid clouds * Use common code so you can run it across any cloud Who this book is for This book is intended for those planning, designing, and implementing the virtualization/cloud components of the Software-Defined Data Center foundational infrastructure. It helps users to put intelligence in their automation tasks to get self driving data center. It is assumed that the reader has knowledge of, and some familiarity with, virtualization concepts and related topics, including storage, security, and networking.

Build modern day application by implementing Material Design principles in React applications using Material-UI. Key Features * Grasp the needs React components for UI elements * Master the style and theme of the tools to go along with these components * Get to grips with all the React best practices to build a modern application Book Description Material-UI is a component library for rendering UI elements, using modern best practices from React and Material Design. This book will show you how you can create impressive and captivating modern day web apps by implementing Material Design considerations. The primary objective of this book is to help you use several Material-UI components to build larger UI functionality. We will also focus on React best practices in conjunction with Material-UI components – using state, context, and other new React 16.8 features properly. This book will start with layout and navigation and then dive into presenting the information with Material-UI components. It will then talk about the different components for user interactions. By the end of this book, you will know how to improve the look and feel of your applications using Material-UI components. What you will learn * Learn to build the overall structure and navigation for your Material-UI app * Learn to present simple and complex information in a variety of ways * Build interactive and intuitive controls * Design portable themes and styles for all of your Material-UI apps * Group content into sections using tabs and expansion panels * Learn how to design a general page layout with Material-UI grids * Use lists for complex data, and cards for detailed information Who this book is for They are JavaScript developers who have some basic knowledge of React and would want to implement Material Design principles in React applications using Material-UI. The reader wants to build a user interface using React components but doesn’t want to invent their own style or UX framework.

Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key Features * Study new techniques for marketing analytics * Explore uses of machine learning to power your marketing analyses * Work through each stage of data analytics with the help of multiple examples and exercises Book Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learn * Analyze and visualize data in Python using pandas and Matplotlib * Study clustering techniques, such as hierarchical and k-means clustering * Create customer segments based on manipulated data * Predict customer lifetime value using linear regression * Use classification algorithms to understand customer choice * Optimize classification algorithms to extract maximal information Who this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.

Enhance your programming skills to build exciting robotic projects Key Features * Build an intelligent robot that can detect and avoid obstacles and respond to voice commands * Detect and track objects and faces using OpenCV * Control your robot with a GUI button designed using Qt5 Book Description C++ is one of the most popular legacy programming languages for robotics, and a combination of C++ and robotics hardware is used in many leading industries. This book will bridge the gap between Raspberry Pi and C/C++ programming and enable you to develop applications for Raspberry Pi. To follow along with the projects covered in the book, you can implement C programs in Raspberry Pi with the wiringPi library. With this book, you’ll develop a fully functional car robot and write programs to move it in different directions. You’ll then create an obstacle - avoiding robot using an ultrasonic sensor. Furthermore, you’ll find out how to control the robot wirelessly using your PC/Mac. This book will also help you work with object detection and tracking using OpenCV, and guide you through exploring face detection techniques. Finally, you will create an Android app and control the robot wirelessly with an Android smartphone. By the end of this book, you will have gained experience in developing a robot using Raspberry Pi and C/C++ programming. What you will learn * Install software in Raspberry Pi compatible with C++ programming * Program the Raspberry Pi in C++ to run a motor * Control RPi-powered robot wirelessly with your laptop or PC * Program an RPi camera using OpenCV Control a Raspberry Pi robot with voice commands * Implement face and object detection with Raspberry Pi Who this book is for This book is for developers, programmers, and robotics enthusiasts interested in leveraging C++ to build exciting robotics applications. Prior knowledge of C++ is necessary to understand the projects covered in this book.

Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features * Learn and implement machine learning algorithms in a variety of real-life scenarios * Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques * Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn * Use predictive modeling and apply it to real-world problems * Explore data visualization techniques to interact with your data * Learn how to build a recommendation engine * Understand how to interact with text data and build models to analyze it * Work with speech data and recognize spoken words using Hidden Markov Models * Get well versed with reinforcement learning, automated ML, and transfer learning * Work with image data and build systems for image recognition and biometric face recognition * Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.

Get to grips with programming techniques and game development using C++ libraries and Visual Studio 2019 Key Features * Learn game development and C++ with a fun, example-driven approach * Build clones of popular games such as Timberman, Zombie Survival Shooter, a co-op puzzle platformer, and Space Invaders * Discover tips to expand your finished games by thinking critically, technically, and creatively Book Description The second edition of Beginning C++ Game Programming is updated and improved to include the latest features of Visual Studio 2019, SFML, and modern C++ programming techniques. With this book, you’ll get a fun introduction to game programming by building five fully playable games of increasing complexity. You’ll learn to build clones of popular games such as Timberman, Pong, a Zombie survival shooter, a coop puzzle platformer and Space Invaders. The book starts by covering the basics of programming. You’ll study key C++ topics, such as object-oriented programming (OOP) and C++ pointers, and get acquainted with the Standard Template Library (STL). The book helps you learn about collision detection techniques and game physics by building a Pong game. As you build games, you’ll also learn exciting game programming concepts such as particle effects, directional sound (spatialization), OpenGL programmable shaders, spawning objects, and much more. Finally, you’ll explore game design patterns to enhance your C++ game programming skills. By the end of the book, you’ll have gained the knowledge you need to build your own games with exciting features from scratch What you will learn * Set up your game development project in Visual Studio 2019 and explore C++ libraries such as SFML * Explore C++ OOP by building a Pong game * Understand core game concepts such as game animation, game physics, collision detection, scorekeeping, and game sound * Use classes, inheritance, and references to spawn and control thousands of enemies and shoot rapid-fire machine guns * Add advanced features to your game using pointers, references, and the STL * Scale and reuse your game code by learning modern game programming design patterns Who this book is for This book is perfect for you if you have no C++ programming knowledge, you need a beginner-level refresher course, or you want to learn how to build games or just use games as an engaging way to learn C++. Whether you aspire to publish a game (perhaps on Steam) or just want to impress friends with your creations, you’ll find this book useful.

Learn the fundamentals, practical applications, and latest features of C# 8.0 and .NET Core 3.0 from expert teacher Mark J. Price. Key Features * Build modern, cross-platform applications with .NET Core 3.0 * Get up to speed with C#, and up to date with all the latest features of C# 8.0 * Start creating professional web applications with ASP.NET Core 3.0 Book Description In C# 8.0 and .NET Core 3.0 – Modern Cross-Platform Development, Fourth Edition, expert teacher Mark J. Price gives you everything you need to start programming C# applications. This latest edition uses the popular Visual Studio Code editor to work across all major operating systems. It is fully updated and expanded with new chapters on Content Management Systems (CMS) and machine learning with ML.NET. The book covers all the topics you need. Part 1 teaches the fundamentals of C#, including object-oriented programming, and new C# 8.0 features such as nullable reference types, simplified switch pattern matching, and default interface methods. Part 2 covers the .NET Standard APIs, such as managing and querying data, monitoring and improving performance, working with the filesystem, async streams, serialization, and encryption. Part 3 provides examples of cross-platform applications you can build and deploy, such as web apps using ASP.NET Core or mobile apps using Xamarin.Forms. The book introduces three technologies for building Windows desktop applications including Windows Forms, Windows Presentation Foundation (WPF), and Universal Windows Platform (UWP) apps, as well as web applications, web services, and mobile apps. What you will learn * Build cross-platform applications for Windows, macOS, Linux, iOS, and Android * Explore application development with C# 8.0 and .NET Core 3.0 * Explore ASP.NET Core 3.0 and create professional web applications * Learn object-oriented programming and C# multitasking * Query and manipulate data using LINQ * Use Entity Framework Core and work with relational databases * Discover Windows app development using the Universal Windows Platform and XAML * Build mobile applications for iOS and Android using Xamarin.Forms Who this book is for Readers with some prior programming experience or with a science, technology, engineering, or mathematics (STEM) background, who want to gain a solid foundation with C# 8.0 and .NET Core 3.0.

Machines can LEARN ?!?! Machine learning occurs primarily through the use of " algorithms" and other elaborate procedures Whether you're a novice, intermediate or expert this book will teach you all the ins, outs and everything you need to know about machine learning Note: Bonus chapters included inside! Instead of spending hundreds or even thousands of dollars on courses/materials why not read this book instead? Its a worthwhile read and the most valuable investment you can make for yourself Other books easily retail for $50-$100+ and have far less quality content. This book is by far superior and exceeds any other book available for beginners. What You'll Learn Supervised Learning Unsupervised Learning Reinforced Learning Algorithms Decision Tree Random Forest Neural Networks Python Deep Learning And much, much more! This is the most comprehensive and easy to read step by step guide in machine learning that exists. Learn from one of the most reliable programmers alive and expert in the field You do not want to miss out on this incredible offer!

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