Information Theory. A Tutorial Introduction to the Principles and Applications of Information Theory

This book offers a comprehensive journey through the fascinating world of information theory, beginning with the fundamental question: what is information? Early chapters introduce key concepts like entropy, binary representation, and data compression, providing a clear and accessible foundation. Readers explore Shannon's source coding theorem and practical tools like Huffman coding to understand how information is quantified and optimized.Building on these basics, the book delves into advanced topics such as the noisy channel coding theorem, mutual information, and error correction techniques. It examines entropy in continuous systems, channel capacity, and rate-distortion theory, making complex ideas accessible through real-world examples. Connections between information and thermodynamics are also explored, including Maxwell’s Demon, the Landauer Limit, and the second law of thermodynamics.The final chapters tie information theory to biology and artificial intelligence, investigating its role in evolution, the human genome, and brain computation. With practical examples throughout, this book balances theoretical depth with hands-on learning, making it an essential resource for mastering information theory. A basic mathematical foundation will be beneficial but is not required to engage with the material.

3D Environment Design with Blender. Enhance your modeling, texturing, and lighting skills to create realistic 3D scenes

Abdelilah Hamdani, Carlos Barreto

Blender is a powerful tool for creating all kinds of visual assets, but with such power comes complexity. Creating a photorealistic 3D scene seems like a Herculean task for more than 90% of 3D designers, but don’t be discouraged! 3D Environment Design with Blender will get you up and running.This practical guide helps reduce the complexity of 3D environment design, advance your Blender skills, and produce lifelike scenes and animations in a time-efficient manner. You'll start by learning how to fix the most common mistakes 3D designers make with modeling and scale matching that stop them from achieving photorealism. Next, you’ll understand the basics of realistic texturing, efficient unwrapping and achieving photorealistic lighting by turning an actual reference of a wood cabin into a realistic 3D scene. These skills will be used and expanded as you build a realistic 3D environment with natural assets and materials that you’ll create from scratch. Once you’ve developed your natural environment, you’ll advance to creating realistic render shots by applying cool camera features, and compositing tricks that will make your final render look photorealistic and pleasing to the eye.By the end of this book, you'll be able to implement modeling tricks and best practices to make your 3D environments look stunningly lifelike.

Mastering Eclipse Plug-in Development. Build modular applications on Eclipse by defining custom extension points and using OSGi services

Bandlem Limited

ArcGIS Pro 3.x Cookbook. Create, manage, analyze, maintain, and visualize geospatial data using ArcGIS Pro - Second Edition

Tripp Corbin, GISP, Kirk Larson

ArcGIS Pro, Esri's newest desktop GIS application, offers powerful tools for visualizing, maintaining, and analyzing data. This cookbook will help existing ArcMap users transition to ArcGIS Pro and teach new users how to utilize its GIS tools effectively. You’ll learn how to create geodatabases, convert data formats, link tables from outside sources, edit 2D and 3D data, ensure data integrity with topology, and enable advanced geodatabase behavior. By the end, you'll be able to effectively use ArcGIS Pro as your primary desktop GIS application, maintaining, analyzing, and displaying data using common methods and tools.

Building Mapping Applications with QGIS. Create your own sophisticated applications to analyze and display geospatial information using QGIS and Python

Erik Westra

The Complete Rust Programming Reference Guide. Design, develop, and deploy effective software systems using the advanced constructs of Rust

Rahul Sharma, Vesa Kaihlavirta, Claus Matzinger

Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs.You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code.This Learning Path includes content from the following Packt products:• Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta• Hands-On Data Structures and Algorithms with Rust by Claus Matzinger

Real-time Analytics with Storm and Cassandra. Solve real-time analytics problems effectively using Storm and Cassandra

Shilpi Saxena

Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition

Andrew P. McMahon, Adi Polak

The Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field.The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You'll explore the key steps of the ML development lifecycle and create your own standardized model factory for training and retraining of models. You'll learn to employ concepts like CI/CD and how to detect different types of drift.Get hands-on with the latest in deployment architectures and discover methods for scaling up your solutions. This edition goes deeper in all aspects of ML engineering and MLOps, with emphasis on the latest open-source and cloud-based technologies. This includes a completely revamped approach to advanced pipelining and orchestration techniques.With a new chapter on deep learning, generative AI, and LLMOps, you will learn to use tools like LangChain, PyTorch, and Hugging Face to leverage LLMs for supercharged analysis. You will explore AI assistants like GitHub Copilot to become more productive, then dive deep into the engineering considerations of working with deep learning.