Microsoft Dynamics AX 2012 R2 Services. Using Microsoft Dynamics AX to create and run your own services is made plain sailing with this in-depth tutorial. Covering everything from document services to building customized services and batch processing, it’s the complete guide

Saelen Kenny, Klaas Deforche

A Handbook of Mathematical Models with Python. Elevate your machine learning projects with NetworkX, PuLP, and linalg

Dr. Ranja Sarkar

Mathematical modeling is the art of transforming a business problem into a well-defined mathematical formulation. Its emphasis on interpretability is particularly crucial when deploying a model to support high-stake decisions in sensitive sectors like pharmaceuticals and healthcare.Through this book, you’ll gain a firm grasp of the foundational mathematics underpinning various machine learning algorithms. Equipped with this knowledge, you can modify algorithms to suit your business problem. Starting with the basic theory and concepts of mathematical modeling, you’ll explore an array of mathematical tools that will empower you to extract insights and understand the data better, which in turn will aid in making optimal, data-driven decisions. The book allows you to explore mathematical optimization and its wide range of applications, and concludes by highlighting the synergetic value derived from blending mathematical models with machine learning.Ultimately, you’ll be able to apply everything you’ve learned to choose the most fitting methodologies for the business problems you encounter.

Oracle Cloud Infrastructure for Solutions Architects. A practical guide to effectively designing enterprise-grade solutions with OCI services

Prasenjit Sarkar, Guillermo Ruiz

Oracle Cloud Infrastructure (OCI) is a set of complementary cloud services that enables you to build and run a wide range of applications and services in a highly available hosted environment. This book is a fast-paced practical guide that will help you develop the capabilities to leverage OCI services and effectively manage your cloud infrastructure.Oracle Cloud Infrastructure for Solutions Architects begins by helping you get to grips with the fundamentals of Oracle Cloud Infrastructure, and moves on to cover the building blocks of the layers of Infrastructure as a Service (IaaS), such as Identity and Access Management (IAM), compute, storage, network, and database. As you advance, you’ll delve into the development aspects of OCI, where you’ll learn to build cloud-native applications and perform operations on OCI resources as well as use the CLI, API, and SDK. Finally, you’ll explore the capabilities of building an Oracle hybrid cloud infrastructure.By the end of this book, you’ll have learned how to leverage the OCI and gained a solid understanding of the persona of an architect as well as a developer’s perspective.

Moodle Theme Development. Click here to enter text

Silvina Paola Hillar

Theming is one of the main features of Moodle, and it can be used to customize your online courses and make them look exactly how you want them to,according to your target audience. If you have been looking for a book that will help you develop Moodle themes that you are proud of, and that your students will enjoy, then this is the book for you.We start off by introducing Moodle 3 and explaining what it is, how it works, and what tools you might need to create a stunning Moodle theme. We then show you how to choose and change the pre-installed Moodle themes in detailed steps, and explain what Moodle themes are and how they work. Next, we show you how to change an existing theme and test the changes that you have made.You can not only plan the customization of theme, but also tailor it using advanced Moodle theming processes; this book is your one-stop guide to creating your own personalized Moodle 3 theme.

Big Data Analytics with R. Leverage R Programming to uncover hidden patterns in your Big Data

Simon Walkowiak

Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing.The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.

OpenGL 4.0 Shading Language Cookbook. With over 60 recipes, this Cookbook will teach you both the elementary and finer points of the OpenGL Shading Language, and get you familiar with the specific features of GLSL 4.0. A totally practical, hands-on guide

David Wolff, OpenGL

The OpenGL Shading Language (GLSL) is a programming language used for customizing parts of the OpenGL graphics pipeline that were formerly fixed-function, and are executed directly on the GPU. It provides programmers with unprecedented flexibility for implementing effects and optimizations utilizing the power of modern GPUs. With version 4.0, the language has been further refined to provide programmers with greater flexibility, and additional features have been added such as an entirely new stage called the tessellation shader.The OpenGL Shading Language 4.0 Cookbook provides easy-to-follow examples that first walk you through the theory and background behind each technique then go on to provide and explain the GLSL and OpenGL code needed to implement it. Beginning level through to advanced techniques are presented including topics such as texturing, screen-space techniques, lighting, shading, tessellation shaders, geometry shaders, and shadows.The OpenGL Shading Language 4.0 Cookbook is a practical guide that takes you from the basics of programming with GLSL 4.0 and OpenGL 4.0, through basic lighting and shading techniques, to more advanced techniques and effects. It presents techniques for producing basic lighting and shading effects; examples that demonstrate how to make use of textures for a wide variety of effects and as part of other techniques; examples of screen-space techniques, shadowing, tessellation and geometry shaders, noise, and animation.The OpenGL Shading Language 4.0 Cookbook provides examples of modern shading techniques that can be used as a starting point for programmers to expand upon to produce modern, interactive, 3D computer graphics applications.

Machine Learning: Make Your Own Recommender System. Build Your Recommender System with Machine Learning Insights

Oliver Theobald

With an introductory overview, the course prepares you for a deep dive into the practical application of Scikit-Learn and the datasets that bring theories to life. From the basics of machine learning to the intricate details of setting up a sandbox environment, this course covers the essential groundwork for any aspiring data scientist.The course focuses on developing your skills in working with data, implementing data reduction techniques, and understanding the intricacies of item-based and user-based collaborative filtering, along with content-based filtering. These core methodologies are crucial for creating accurate and efficient recommender systems that cater to the unique preferences of users. Practical examples and evaluations further solidify your learning, making complex concepts accessible and manageable.The course wraps up by addressing the critical topics of privacy, ethics in machine learning, and the exciting future of recommender systems. This holistic approach ensures that you not only gain technical proficiency but also consider the broader implications of your work in this field. With a final look at further resources, your journey into machine learning and recommender systems is just beginning, armed with the knowledge and tools to explore new horizons.

Hands-On Enterprise Automation on Linux. Efficiently perform large-scale Linux infrastructure automation with Ansible

James Freeman

Automation is paramount if you want to run Linux in your enterprise effectively. It helps you minimize costs by reducing manual operations, ensuring compliance across data centers, and accelerating deployments for your cloud infrastructures.Complete with detailed explanations, practical examples, and self-assessment questions, this book will teach you how to manage your Linux estate and leverage Ansible to achieve effective levels of automation. You'll learn important concepts on standard operating environments that lend themselves to automation, and then build on this knowledge by applying Ansible to achieve standardization throughout your Linux environments.By the end of this Linux automation book, you'll be able to build, deploy, and manage an entire estate of Linux servers with higher reliability and lower overheads than ever before.