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Practical Deep Learning at Scale with MLflow. Bridge the gap between offline experimentation and online production

Yong Liu, Dr. Matei Zaharia

The book starts with an overview of the deep learning (DL) life cycle and the emerging Machine Learning Ops (MLOps) field, providing a clear picture of the four pillars of deep learning: data, model, code, and explainability and the role of MLflow in these areas.From there onward, it guides you step by step in understanding the concept of MLflow experiments and usage patterns, using MLflow as a unified framework to track DL data, code and pipelines, models, parameters, and metrics at scale. You’ll also tackle running DL pipelines in a distributed execution environment with reproducibility and provenance tracking, and tuning DL models through hyperparameter optimization (HPO) with Ray Tune, Optuna, and HyperBand. As you progress, you’ll learn how to build a multi-step DL inference pipeline with preprocessing and postprocessing steps, deploy a DL inference pipeline for production using Ray Serve and AWS SageMaker, and finally create a DL explanation as a service (EaaS) using the popular Shapley Additive Explanations (SHAP) toolbox.By the end of this book, you’ll have built the foundation and gained the hands-on experience you need to develop a DL pipeline solution from initial offline experimentation to final deployment and production, all within a reproducible and open source framework.

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Practical Design Patterns for Java Developers. Hone your software design skills by implementing popular design patterns in Java

Miroslav Wengner, Bruno Souza

Design patterns are proven solutions to standard problems in software design and development, allowing you to create reusable, flexible, and maintainable code. This book enables you to upskill by understanding popular patterns to evolve into a proficient software developer.You’ll start by exploring the Java platform to understand and implement design patterns. Then, using various examples, you’ll create different types of vehicles or their parts to enable clarity in design pattern thinking, along with developing new vehicle instances using dedicated design patterns to make the process consistent. As you progress, you’ll find out how to extend vehicle functionalities and keep the code base structure and behavior clean and shiny. Concurrency plays an important role in application design, and you'll learn how to employ a such design patterns with the visualization of thread interaction. The concluding chapters will help you identify and understand anti-pattern utilization in the early stages of development to address refactoring smoothly. The book covers the use of Java 17+ features such as pattern matching, switch cases, and instances of enhancements to enable productivity.By the end of this book, you’ll have gained practical knowledge of design patterns in Java and be able to apply them to address common design problems.

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Practical DevOps. Harness the power of DevOps to boost your skill set and make your IT organization perform better

joakim verona

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all the flows from code through testing environments to production environments. It stresses the cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations.After a quick refresher to DevOps and continuous delivery, we quickly move on to looking at how DevOps affects architecture. You'll create a sample enterprise Java application that you’ll continue to work with through the remaining chapters. Following this, we explore various code storage and build server options. You will then learn how to perform code testing with a few tools and deploy your test successfully. Next, you will learn how to monitor code for any anomalies and make sure it’s running properly. Finally, you will discover how to handle logs and keep track of the issues that affect processes

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Practical DevOps. Implement DevOps in your organization by effectively building, deploying, testing, and monitoring code - Second Edition

joakim verona

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all code workflows from testing environments to production environments. It stresses cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations.Practical DevOps begins with a quick refresher on DevOps and continuous delivery and quickly moves on to show you how DevOps affects software architectures. You'll create a sample enterprise Java application that you’'ll continue to work with through the remaining chapters. Following this, you will explore various code storage and build server options. You will then learn how to test your code with a few tools and deploy your test successfully. In addition to this, you will also see how to monitor code for any anomalies and make sure that it runs as expected. Finally, you will discover how to handle logs and keep track of the issues that affect different processes.By the end of the book, you will be familiar with all the tools needed to deploy, integrate, and deliver efficiently with DevOps.

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Practical Digital Forensics. Get started with the art and science of digital forensics with this practical, hands-on guide!

Richard Boddington

Digital Forensics is a methodology which includes using various tools, techniques, and programming language. This book will get you started with digital forensics and then follow on to preparing investigation plan and preparing toolkit for investigation.In this book you will explore new and promising forensic processes and tools based on ‘disruptive technology’ that offer experienced and budding practitioners the means to regain control of their caseloads. During the course of the book, you will get to know about the technical side of digital forensics and various tools that are needed to perform digital forensics. This book will begin with giving a quick insight into the nature of digital evidence, where it is located and how it can be recovered and forensically examined to assist investigators. This book will take you through a series of chapters that look at the nature and circumstances of digital forensic examinations and explains the processes of evidence recovery and preservation from a range of digital devices, including mobile phones, and other media. This book has a range of case studies and simulations will allow you to apply the knowledge of the theory gained to real-life situations. By the end of this book you will have gained a sound insight into digital forensics and its key components.

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Practical Discrete Mathematics. Discover math principles that fuel algorithms for computer science and machine learning with Python

Ryan T. White, Archana Tikayat Ray

Discrete mathematics deals with studying countable, distinct elements, and its principles are widely used in building algorithms for computer science and data science. The knowledge of discrete math concepts will help you understand the algorithms, binary, and general mathematics that sit at the core of data-driven tasks.Practical Discrete Mathematics is a comprehensive introduction for those who are new to the mathematics of countable objects. This book will help you get up to speed with using discrete math principles to take your computer science skills to a more advanced level.As you learn the language of discrete mathematics, you’ll also cover methods crucial to studying and describing computer science and machine learning objects and algorithms. The chapters that follow will guide you through how memory and CPUs work. In addition to this, you’ll understand how to analyze data for useful patterns, before finally exploring how to apply math concepts in network routing, web searching, and data science.By the end of this book, you’ll have a deeper understanding of discrete math and its applications in computer science, and be ready to work on real-world algorithm development and machine learning.

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Practical Finite Element Simulations with SOLIDWORKS 2022. An illustrated guide to performing static analysis with SOLIDWORKS Simulation

Khameel B. Mustapha

SOLIDWORKS is a dominant computer-aided design (CAD) software for the 3D modeling, designing, and analysis of components. This book helps you get to grips with SOLIDWORKS Simulation, which is a remarkable and integral part of SOLIDWORKS predominantly deployed for advanced product performance assessment and virtual prototyping.With this book, you'll take a hands-on approach to learning SOLIDWORKS Simulation with the help of step-by-step guidelines on various aspects of the simulation workflow. You'll begin by learning about the requirements for effective simulation of parts and components, along with the idealization of physical components and their representation with finite element models. As you progress through the book, you'll find exercises at the end of each chapter, and you'll be able to download the geometry models used in all the chapters from GitHub. Finally, you’ll discover how to set up finite element simulations for the static analysis of components under various types of loads, and with different types of materials, from simple isotropic to composite, and different boundary conditions.By the end of this SOLIDWORKS 2022 book, you'll be able to conduct basic and advanced static analyses with SOLIDWORKS Simulation and have practical knowledge of how to best use the family of elements in the SOLIDWORKS Simulation library.

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Practical Game AI Programming. Unleash the power of Artificial Intelligence to your game

Micael DaGraça

The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to determine character movement. Next, you’ll learn how AI characters should behave within the environment created.Moving on, you’ll explore how to work with animations. You’ll also plan and create pruning strategies, and create Theta algorithms to find short and realistic looking game paths. Next, you’ll learn how the AI should behave when there is a lot of characters in the same scene.You'll explore which methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions. You’ll discover how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you think differently about AI.