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Sztuczna inteligencja
The importance of machine learning (ML) in art is growing at a rapid pace due to recent advancements in the field, and Magenta is at the forefront of this innovation. With this book, you’ll follow a hands-on approach to using ML models for music generation, learning how to integrate them into an existing music production workflow. Complete with practical examples and explanations of the theoretical background required to understand the underlying technologies, this book is the perfect starting point to begin exploring music generation.The book will help you learn how to use the models in Magenta for generating percussion sequences, monophonic and polyphonic melodies in MIDI, and instrument sounds in raw audio. Through practical examples and in-depth explanations, you’ll understand ML models such as RNNs, VAEs, and GANs. Using this knowledge, you’ll create and train your own models for advanced music generation use cases, along with preparing new datasets. Finally, you’ll get to grips with integrating Magenta with other technologies, such as digital audio workstations (DAWs), and using Magenta.js to distribute music generation apps in the browser.By the end of this book, you'll be well-versed with Magenta and have developed the skills you need to use ML models for music generation in your own style.
Simulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it. The ability to analyze the model as it runs sets simulation modelling apart from other methods used in conventional analyses. This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python. The book begins by helping you get familiarized with the fundamental concepts of simulation modelling, that’ll enable you to understand the various methods and techniques needed to explore complex topics. Data scientists working with simulation models will be able to put their knowledge to work with this practical guide. As you advance, you’ll dive deep into numerical simulation algorithms, including an overview of relevant applications, with the help of real-world use cases and practical examples. You'll also find out how to use Python to develop simulation models and how to use several Python packages. Finally, you’ll get to grips with various numerical simulation algorithms and concepts, such as Markov Decision Processes, Monte Carlo methods, and bootstrapping techniques.By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.
Xun (Brian) Wu, Chuanfeng Zhang, Zhibin (Andrew) Zhang
Hyperledger is an open-source project and creates private blockchain applications for a range of domains. This book will be your desk reference as you explore common and not-so-common challenges faced while building blockchain networks using Hyperledger services.We'll work through all Hyperledger platform modules to understand their services and features and build end-to-end blockchain applications using various frameworks and tools supported by Hyperledger. This book's independent, recipe-based approach (packed with real-world examples) will familiarize you with the blockchain development cycle. From modeling a business network to integrating with various tools, you will cover it all. We'll cover common and not-so-common challenges faced in the blockchain life cycle. Later, we'll delve into how we can interact with the Hyperledger Fabric blockchain, covering all the principles you need to master, such as chaincode, smart contracts, and much more. We'll also address the scalability and security issues currently faced in blockchain development.By the end of this book, you will be able to implement each recipe to plan, design, and create a full-fledged, private, decentralized application to meet organizational needs.
Hyperparameters are an important element in building useful machine learning models. This book curates numerous hyperparameter tuning methods for Python, one of the most popular coding languages for machine learning. Alongside in-depth explanations of how each method works, you will use a decision map that can help you identify the best tuning method for your requirements.You’ll start with an introduction to hyperparameter tuning and understand why it's important. Next, you'll learn the best methods for hyperparameter tuning for a variety of use cases and specific algorithm types. This book will not only cover the usual grid or random search but also other powerful underdog methods. Individual chapters are also dedicated to the three main groups of hyperparameter tuning methods: exhaustive search, heuristic search, Bayesian optimization, and multi-fidelity optimization. Later, you will learn about top frameworks like Scikit, Hyperopt, Optuna, NNI, and DEAP to implement hyperparameter tuning. Finally, you will cover hyperparameters of popular algorithms and best practices that will help you efficiently tune your hyperparameter.By the end of this book, you will have the skills you need to take full control over your machine learning models and get the best models for the best results.
Microsoft Dynamics 365 for Customer Engagement (CE) is one of the leading customer relationship management (CRM) solutions that help companies to effectively communicate with their customers and allows them to transform their marketing strategies. Complete with detailed explanations of the essential concepts and practical examples, this book will guide you through the entire life cycle of implementing Dynamics 365 CE for your organization or clients, and will help you avoid common pitfalls while increasing efficiency at every stage of the project. Starting with the foundational concepts, the book will gradually introduce you to Microsoft Dynamics 365 features, plans, and products. You’ll learn various implementation strategies and requirement gathering techniques, and then design the application architecture by converting your requirements into technical and functional designs. As you advance, you’ll learn how to configure your CRM system to meet your organizational needs, customize Dynamics 365 CE, and extend its capabilities by writing client-side and server-side code. Finally, you’ll integrate Dynamics 365 CE with other applications and explore its business intelligence capabilities. By the end of this Microsoft Dynamics 365 book, you’ll have gained an in-depth understanding of all the key components necessary for successful Dynamics 365 CE implementation.
Shyam Varan Nath, Ann Dunkin, Mahesh Chowdhary, Nital Patel
Digital transformation requires the ability to identify opportunities across industries and apply the right technologies and tools to achieve results. This book is divided into two parts with the first covering what digital transformation is and why it is important. The second part focuses on how digital transformation works.After an introduction to digital transformation, you will explore the transformation journey in logical steps and understand how to build business cases and create productivity benefit statements. Next, you’ll delve into advanced topics relating to overcoming various challenges. Later, the book will take you through case studies in both private and public sector organizations. You’ll explore private sector organizations such as industrial and hi-tech manufacturing in detail and get to grips with public sector organizations by learning how transformation can be achieved on a global scale and how the resident experience can be improved. In addition to this, you will understand the role of artificial intelligence, machine learning and deep learning in digital transformation. Finally, you’ll discover how to create a playbook that can ensure success in digital transformation.By the end of this book, you’ll be well-versed with industrial digital transformation and be able to apply your skills in the real world.
Integrate Lua with C++. Seamlessly integrate Lua scripting to enhance application flexibility
C++ is a popular choice in the developer community for building complex and large-scale performant applications and systems. Often a need arises to extend the system at runtime, without recompiling the whole C++ program. Using a scripting language like Lua can help achieve this goal efficiently.Integrate Lua to C++ is a comprehensive guide to integrating Lua to C++ and will enable you to achieve the goal of extending C++ programs at runtime. You’ll learn, in sequence, how to get and compile the Lua library, the Lua programming language, calling Lua code from C++, and calling C++ code from Lua. In each topic, you’ll practice with code examples, and learn the in-depth mechanisms for smooth working. Throughout the book, the latter examples build on the earlier ones while also acting as a standalone. You’ll learn to implement Lua executor and Lua binding generator, which you can use in your projects directly with further customizations.By the end of this book, you’ll have mastered integrating Lua into C++ and using Lua in your C++ project efficiently, gained the skills to extend your applications at runtime, and achieved dynamic and adaptable C++ development.