Applying Math with Python. Practical recipes for solving computational math problems using Python programming and its libraries

Sam Morley

Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain.The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python’s scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.

Visual Basic Quickstart Guide. Improve your programming skills and design applications that range from basic utilities to complex software

Aspen Olmsted

Whether you’re an absolute beginner or an experienced developer looking to learn the Visual Basic language, this book takes a hands-on approach to guide you through the process. From the very first chapters, you'll delve into writing programs, exploring core concepts such as data types, decision branching, and iteration. Additionally, you’ll get to grips with working with data structures, file I/O, and essential object-oriented principles like inheritance and polymorphism.This book goes beyond the basics to equip you with the skills to read and write code across the entire VB family, spanning VB Script, VBA, VB Classic, and VB.NET, enabling you to handle legacy code maintenance with ease.With clear explanations, practical examples, and hands-on exercises, this book empowers you to tackle real-world software development tasks, whether you're enhancing existing projects or embarking on new ones. It addresses common challenges like distinguishing between the variations of the VB programming language to help you choose the right one for your projects.Don't let VB's extensive legacy daunt you; embrace it with this comprehensive guide that equips you with practical, up-to-date coding skills to overcome the challenges presented by Visual Basic's rich history of over two decades.

Groovy for Domain-specific Languages. Extend and enhance your Java applications with domain-specific scripting in Groovy

Fergal Dearle

HDInsight Essentials. Learn how to build and deploy a modern big data architecture to empower your business

Rajesh Nadipalli

Infinispan Data Grid Platform Definitive Guide. Master Infinispan to create scalable and high-performance applications

Wagner Santos, Wagner R Santos

Web Design Blueprints. Build websites and applications using the latest techniques in modern web development

Benjamin LaGrone, Joshua Blackwood

The book delivers simple instructions on how to design and build modern Web using the latest trends in web development. You will learn how to design responsive websites, created with modern Flat User Interface design patterns, build deep-scrolling websites with parallax 3D effects, and roll-your-own single-page applications. Finally, you'll work through an awesome chapter that combines them all. Each chapter features actual lines of code that you can apply right away.

TensorFlow 2.0 Computer Vision Cookbook. Implement machine learning solutions to overcome various computer vision challenges

Jesús Martínez

Computer vision is a scientific field that enables machines to identify and process digital images and videos. This book focuses on independent recipes to help you perform various computer vision tasks using TensorFlow.The book begins by taking you through the basics of deep learning for computer vision, along with covering TensorFlow 2.x’s key features, such as the Keras and tf.data.Dataset APIs. You’ll then learn about the ins and outs of common computer vision tasks, such as image classification, transfer learning, image enhancing and styling, and object detection. The book also covers autoencoders in domains such as inverse image search indexes and image denoising, while offering insights into various architectures used in the recipes, such as convolutional neural networks (CNNs), region-based CNNs (R-CNNs), VGGNet, and You Only Look Once (YOLO). Moving on, you’ll discover tips and tricks to solve any problems faced while building various computer vision applications. Finally, you’ll delve into more advanced topics such as Generative Adversarial Networks (GANs), video processing, and AutoML, concluding with a section focused on techniques to help you boost the performance of your networks.By the end of this TensorFlow book, you’ll be able to confidently tackle a wide range of computer vision problems using TensorFlow 2.x.

Learning Construct 2. Design and create your own engaging, extensible, and addictive game using Construct 2

Aryadi Subagio