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Author: Alexandre DuBreuil
Publisher: Packt Publishing Ltd
ISBN: 1838825762
Category : Mathematics
Languages : en
Pages : 348
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Book Description
Design and use machine learning models for music generation using Magenta and make them interact with existing music creation tools Key FeaturesLearn how machine learning, deep learning, and reinforcement learning are used in music generationGenerate new content by manipulating the source data using Magenta utilities, and train machine learning models with itExplore various Magenta projects such as Magenta Studio, MusicVAE, and NSynthBook Description 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. What you will learnUse RNN models in Magenta to generate MIDI percussion, and monophonic and polyphonic sequencesUse WaveNet and GAN models to generate instrument notes in the form of raw audioEmploy Variational Autoencoder models like MusicVAE and GrooVAE to sample, interpolate, and humanize existing sequencesPrepare and create your dataset on specific styles and instrumentsTrain your network on your personal datasets and fix problems when training networksApply MIDI to synchronize Magenta with existing music production tools like DAWsWho this book is for This book is for technically inclined artists and musically inclined computer scientists. Readers who want to get hands-on with building generative music applications that use deep learning will also find this book useful. Although prior musical or technical competence is not required, basic knowledge of the Python programming language is assumed.
Author: Alexandre DuBreuil
Publisher: Packt Publishing Ltd
ISBN: 1838825762
Category : Mathematics
Languages : en
Pages : 348
Get Book
Book Description
Design and use machine learning models for music generation using Magenta and make them interact with existing music creation tools Key FeaturesLearn how machine learning, deep learning, and reinforcement learning are used in music generationGenerate new content by manipulating the source data using Magenta utilities, and train machine learning models with itExplore various Magenta projects such as Magenta Studio, MusicVAE, and NSynthBook Description 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. What you will learnUse RNN models in Magenta to generate MIDI percussion, and monophonic and polyphonic sequencesUse WaveNet and GAN models to generate instrument notes in the form of raw audioEmploy Variational Autoencoder models like MusicVAE and GrooVAE to sample, interpolate, and humanize existing sequencesPrepare and create your dataset on specific styles and instrumentsTrain your network on your personal datasets and fix problems when training networksApply MIDI to synchronize Magenta with existing music production tools like DAWsWho this book is for This book is for technically inclined artists and musically inclined computer scientists. Readers who want to get hands-on with building generative music applications that use deep learning will also find this book useful. Although prior musical or technical competence is not required, basic knowledge of the Python programming language is assumed.
Author: Jean-Pierre Briot
Publisher: Springer
ISBN: 3319701630
Category : Computers
Languages : en
Pages : 284
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Book Description
This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.
Author: Peter Brinkmann
Publisher: "O'Reilly Media, Inc."
ISBN: 1449331394
Category : Computers
Languages : en
Pages : 124
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Book Description
Want to turn your mobile device into a musical instrument? Or equip your game with interactive audio, rather than canned samples? You can do it with Pure Data (Pd), an open source visual programming environment that lets you manipulate digital audio in real time. This concise book shows you how to use Pd—with help from the libpd library—as an easily embeddable and widely portable sound engine. Whether you’re an audio developer looking to create musical apps with sophisticated audio capabilities, or an application developer ready to enhance mobile games with real-time procedural audio, Making Musical Apps introduces you to Pd and libpd, and provides hands-on instructions for creating musical apps for Android and iOS. Get a crash course in Pd, and discover how to generate and control sounds Learn how to create and deploy algorithmic compositions that react to a user’s activity and environment Use Java or Objective-C to integrate Pd and libpd into mobile apps Learn the steps necessary to build libpd-based apps for Android and iOS
Author: Jeffrey Jackovich
Publisher:
ISBN: 9781789806199
Category : Computers
Languages : en
Pages : 254
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Book Description
Use artificial intelligence and machine learning on AWS to create engaging applications Key Features Explore popular AI and ML services with their underlying algorithms Use the AWS environment to manage your AI workflow Reinforce key concepts with hands-on exercises using real-world datasets Book Description Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models. By the end of this book, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects. What you will learn Get up and running with machine learning on the AWS platform Analyze unstructured text using AI and Amazon Comprehend Create a chatbot and interact with it using speech and text input Retrieve external data via your chatbot Develop a natural language interface Apply AI to images and videos with Amazon Rekognition Who this book is for Machine Learning with AWS is ideal for data scientists, programmers, and machine learning enthusiasts who want to learn about the artificial intelligence and machine learning capabilities of Amazon Web Services.
Author: Giuseppe Ciaburro
Publisher: Packt Publishing Ltd
ISBN: 1788398874
Category : Computers
Languages : en
Pages : 489
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Book Description
Unleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy
Author: Faith S. Holsaert
Publisher: University of Illinois Press
ISBN: 0252098870
Category : History
Languages : en
Pages : 656
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Book Description
In Hands on the Freedom Plow, fifty-two women--northern and southern, young and old, urban and rural, black, white, and Latina--share their courageous personal stories of working for the Student Nonviolent Coordinating Committee (SNCC) on the front lines of the Civil Rights Movement. The testimonies gathered here present a sweeping personal history of SNCC: early sit-ins, voter registration campaigns, and freedom rides; the 1963 March on Washington, the Mississippi Freedom Summer, and the movements in Alabama and Maryland; and Black Power and antiwar activism. Since the women spent time in the Deep South, many also describe risking their lives through beatings and arrests and witnessing unspeakable violence. These intense stories depict women, many very young, dealing with extreme fear and finding the remarkable strength to survive. The women in SNCC acquired new skills, experienced personal growth, sustained one another, and even had fun in the midst of serious struggle. Readers are privy to their analyses of the Movement, its tactics, strategies, and underlying philosophies. The contributors revisit central debates of the struggle including the role of nonviolence and self-defense, the role of white people in a black-led movement, and the role of women within the Movement and the society at large. Each story reveals how the struggle for social change was formed, supported, and maintained by the women who kept their "hands on the freedom plow." As the editors write in the introduction, "Though the voices are different, they all tell the same story--of women bursting out of constraints, leaving school, leaving their hometowns, meeting new people, talking into the night, laughing, going to jail, being afraid, teaching in Freedom Schools, working in the field, dancing at the Elks Hall, working the WATS line to relay horror story after horror story, telling the press, telling the story, telling the word. And making a difference in this world."
Author: Romain Caudron
Publisher: Packt Publishing Ltd
ISBN: 1787122468
Category : Computers
Languages : en
Pages : 1281
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Book Description
Build your very own stunning characters in Blender from scratch About This Book Packed with illustrations and a lot of tips and tricks to make your scenes come to life Design a complete workflow with Blender to create stunning 3D scenes and films step by step Gain an understanding of how to create and assign materials automatically, working in both the Blender Internal engine as well as in Cycles Who This Book Is For If you are a graphic designer and are looking for a tool to meet your requirements in designing, especially with regards to 3D designing, this course is for you. This course will make use of Blender to meet your design needs. What You Will Learn Understand the basics of 3D and how to navigate your way around the Blender interface Discover the power of the texture paint tool in order to add color to a haunted house Get to know the Cycles render engine by creating different materials for the house and the environment Find the best possible flow for your edge-loops to enhance the character features and to get the best possible range of deformation Mix both the Blender Internal and Cycles rendering engines in order to render materials as quickly as possible Set up light sources and world global illumination Build material interfaces for general use in complex materials by grouping the shaders inside groups Parent and rename the nodes to better organize the Node Editor window In Detail Blender is a powerful, stable tool with an integral workflow that will allow you to understand 3D creation with ease. With its integrated game engine and use of the Python language, it is an efficient choice for many productions, including 3D animated or live action films, architecture, research, and even game creation. Blender has an active community that contributes to expanding its functionalities. Today, it is used in many professional products and by many companies. Throughout Blender for Designers, you will create many types of complete projects using a step-by-step approach. Start by getting to know the modeling tools available in Blender to create a 3D robot toy, and discover more advanced techniques such as sculpting and retopology by creating an alien character. Move on in the second module to engage with the workflow used to create characters. Run through the process from modeling to the rendering stages, using the tools of the latest official release of Blender. The last module will teach you how to utilize the power of the Blender series to create a wide variety of materials, textures, and effects using the Cycles rendering engine. You will learn about node-based shader creation, and master Cycles through step-by-step, recipe-based advice. Start small by rendering the textures of stones and water, then scale things up to massive landscapes of mountains and oceans. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Blender 3D By Example By Romain Caudron and Pierre-Armand Nicq Blender 3D Cookbook By Enrico Valenza Blender Cycles: Materials and Textures Cookbook - Third Edition By Enrico Valenza Style and approach The course starts with a step-by-step approach to creating concert projects and help you understand the basics of it. With the guided explanation throughout this, each topic is explained with an example.
Author: Francois Chollet
Publisher: Simon and Schuster
ISBN: 1638352046
Category : Computers
Languages : en
Pages : 597
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Book Description
Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance
Author: Christopher Pitt
Publisher: Packt Publishing Ltd
ISBN: 1785883720
Category : Computers
Languages : en
Pages : 182
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Book Description
Explore the power of React components for cutting-edge web development About This Book Learn to build better websites by creating a variety of different components in React Conceptualize the design and build maintainable web apps with the help of components A fast-paced guide to help you learn about component-based development in React Who This Book Is For This book is ideal for developers who are familiar with the basics of React and are looking for a guide to building a wide range of components as well as develop component-driven UIs. What You Will Learn How to structure an app into components Working with nested components Work with nested components Set up communication across components Style the existing components Work with Material Design as a component Render components on the server Make the best of design patterns Make the app pluggable In Detail The reader will learn how to use React and its component-based architecture in order to develop modern user interfaces. A new holistic way of thinking about UI development will establish throughout this book and the reader will discover the power of React components with many examples. After reading the book and following the example application, the reader has built a small to a mid-size application with React using a component based UI architecture. The book will take the reader through a journey to discover the benefits of component-based user interfaces over the classical MVC architecture. Throughout the book, the reader will develop a wide range of components and then bring them together to build a component-based UI. By the end of this book, readers would have learned several techniques to build powerful components and how the component-based development is beneficial over regular web development. Style and approach This book is a compact, example-driven guide that provides a step-by-step approach.
Author: Joshua Au-Yeung
Publisher: Packt Publishing Ltd
ISBN: 180056337X
Category : Music
Languages : en
Pages : 336
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Book Description
Leverage the power of FL Studio 20 to create and compose production-quality songs and develop professional music production skills Key Features Leverage the power of FL Studio to create your own production-level music Develop widely applicable music production skills and learn how to promote your music Utilize cutting-edge tools to fuel your creative ideas and publish your songs Book DescriptionFL Studio is a cutting-edge software music production environment and an extremely powerful and easy-to-use tool for creating music. This book will give you everything you need to produce music with FL Studio like a professional. You'll begin by exploring FL Studio 20's vast array of tools, and discover best practices, tips, and tricks for creating music. You'll then learn how to set up your studio environment, create a beat, compose a melody and chord progression, mix sounds with effects, and export songs. As you advance, you'll find out how to use tools such as the Piano roll, mixer console, audio envelopes, types of compression, equalizers, vocoders, vocal chops, and tools for increasing stereo width. The book introduces you to mixing best practices, and shows you how to master your songs. Along the way, you'll explore glitch effects and create your own instruments and custom-designed effect chains. You'll also cover ZGameEditor Visualizer, a tool used for creating reactive visuals for your songs. Finally, you'll learn how to register, sell, and promote your music. By the end of this FL Studio book, you'll be able to utilize cutting-edge tools to fuel your creative ideas, mix music effectively, and publish your songs.What you will learn Get up and running with FL Studio 20 Record live instruments and vocals and process them Compose melodies and chord progressions on the Piano roll Discover mixing techniques and apply effects to your tracks Explore best practices to produce music like a professional Publish songs in online stores and promote your music effectively Who this book is for This book is for music producers, composers, songwriters, DJs, and audio engineers interested in creating their own music, improving music production skills, mixing and mastering music, and selling songs online. To get started with this book, all you need is a computer and FL Studio.
