Luiz barry (14 Ergebnisse)
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Perspectives in Musicology:
Edited by Barry Brook, Edward Downes, and Sherman van Solkema; Contributing authors: Gustave Reese, Friedrich Blume, Vincent Duckles, Francois Lesure, Emanuel Winternitz, Edward Lowinsky, H.C. Robbins Landon, Milton Babbitt, Paul Henry Lang, Gilbert Chase, Georg Knepler, Luiz Heitor Correa de Azevedo, J.H. Kwabena Nketia, Mantle Hood, Frank Harrison, and Barry Brook.
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Softcover. The Norton Library. xvi, 365 pp. Softcover. LCC: 78103964 Good condition; on covers: light yellowing, and touches of wear on edges; light fading on pages.
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Perspectives in Musicology:
Edited by Barry Brook, Edward Downes, and Sherman Van Solkema; Introduction and Bibliography by Barry Brook; Participating Lecturers: Luiz Heitor Correa de Azevedo, Milton Babbitt, Friedrich Blume, Gilbert Chase, Vincent Duckles, Frank Harrison, Mantle Hood, Georg Knepler, Howard Chandler Robbins Landon, Paul Henry Lang, Francoise Lesure, Edward Lowinsky, J.H. Kwabena Nketia, Gustave Reese, and Emanuel Winternitz.
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Softcover. Zustand: Good condition. Norton Library. The Inaugural Lectures of the Ph.D. Program in Music at the City University of New York. xvi, 365 pp. Softcover. LCC: 78103964.
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Taschenbuch. Zustand: Neu. Neuware - Ready to dive into the revolutionary world of Deep Learning but feeling overwhelmed This book is your friendly, hands-on guide to mastering PyTorch, the powerful and intuitive Python framework that's transforming artificial intelligence.
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Paperback. Zustand: new. Paperback. Harness the Power of PyTorch for Cutting-Edge AI SolutionsPyTorch has become the go-to deep learning framework for researchers and industry professionals alike. Whether you're a data scientist, AI engineer, or Python enthusiast, this book will help you master PyTorch and apply it to real-world… machine learning and deep learning challenges.Master PyTorch for AI and Data ScienceThis comprehensive guide takes you from the fundamentals of PyTorch to advanced deep learning techniques, enabling you to build, train, and optimize models with confidence. You'll start with an introduction to tensors and autograd, then progress to training neural networks, fine-tuning transformers, and deploying AI models. With practical examples and hands-on projects, you'll gain a deep understanding of PyTorch's capabilities for natural language processing (NLP), computer vision, and structured data tasks.By the end of this book, you'll be equipped with the skills to develop scalable, production-ready AI models using PyTorch, making you a valuable asset in the world of data science and machine learning.Why Choose This Book? Practical Approach - Learn through real-world projects and hands-on exercises. Comprehensive Coverage - Covers everything from basic tensors to advanced deep learning architectures. Modern AI Techniques - Includes transformers, GANs, and reinforcement learning. Optimized for Efficiency - Learn best practices for model optimization and deployment. Perfect for Data Scientists - Tailored for those looking to apply machine learning to real-world datasets.Start Building Smarter AI Models Today!Don't just learn PyTorch-master it with this practical, in-depth guide. Grab your copy now and take your data science and AI skills to the next level! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Zustand: new. Paperback. Ready to dive into the revolutionary world of Deep Learning but feeling overwhelmed? This book is your friendly, hands-on guide to mastering PyTorch, the powerful and intuitive Python framework that's transforming artificial intelligence."PyTorch for Deep Learning: A Practical Introduction for… Beginners" provides a clear and accessible path for anyone with basic Python knowledge to build and train their own deep learning models. You'll start with the fundamentals, learning about tensors, automatic differentiation, and neural network building blocks. The book then guides you through practical examples, including image and text classification, using convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Finally, you'll discover advanced techniques like transfer learning to leverage pre-trained models for rapid development and cutting-edge results. Throughout the book, code examples are clear, well-documented, and designed to help you build real-world applications.This book prioritizes hands-on learning and makes no assumptions about previous machine learning knowledge. Learn to build and train linear regression and logistic regression models, how data is handled by datasets and dataloaders, and how to monitor and evaluate model performance using metrics and visualizations. This book provides practical exercises that reinforce learning and show how to apply what you've learned to real-world problems. This book will help you to gain skills in one of the most indemand AI frameworks.Why Choose This Book?Beginner-Friendly: Assumes no prior machine learning knowledge.Practical Focus: Emphasizes hands-on coding and real-world applications.Clear Explanations: Breaks down complex concepts into simple, easy-to-understand terms.Step-by-Step Guidance: Provides a structured path from foundational concepts to building complete deep learning pipelines.Up-to-Date Content: Covers the latest PyTorch features and best practices.Ready to transform your Python skills into Deep Learning expertise? Grab your copy of "PyTorch for Deep Learning: A Practical Introduction for Beginners" today and start building the future of AI! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
