Deep Learning Crash Course (Paperback)

Name: Deep Learning Crash Course (Paperback)
Author: Giovanni Volpe
ISBN: 9781718503922

Giovanni Volpe

Language: English

Published by No Starch Press,US, San Francisco, 2026

171850392X / 9781718503922

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Paperback. A complete guide to deep neural networks - the technology behind AI - covering fundamental and advanced techniques to apply machine learning in real-world scenarios.Build AI Models from Scratch (No PhD Required)Deep Learning Crash Course is a fast-paced, thorough introduction that will have you building today's most powerful AI models from scratch. No experience with deep learning required!Designed for programmers who may be new to deep learning, this book offers practical, hands-on experience, not just an abstract understanding of theory.You'll start from the basics, and using PyTorch with real datasets, you'll quickly progress from your first neural network to advanced architectures like convolutional neural networks (CNNs), transformers, diffusion models, and graph neural networks (GNNs). Each project can be run on your own hardware or in the cloud, with annotated code available on GitHub.You'll build and train models to:Classify and analyze images, sequences, and time seriesGenerate and transform data with autoencoders, GANs (generative adversarial networks), and diffusion modelsProcess natural language with recurrent neural networks and transformersModel molecules and physical systems with graph neural networksImprove continuously through reinforcement and active learningPredict chaotic systems with reservoir computingWhether you're an engineer, scientist, or professional developer, you'll gain fluency in deep learning and the confidence to apply it to ambitious, real-world problems. With Deep Learning Crash Course, you'll move from using AI tools to creating them. "A comprehensive, hands-on guide to deep learning using Python, combining theoretical concepts with practical examples and step-by-step code implementation. Covers foundational topics as well as advanced subjects such as generative models and reinforcement learning"-- Provided by publisher. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Title: Deep Learning Crash Course (Paperback)
Author: Giovanni Volpe
Publisher: No Starch Press,US, San Francisco
Publication year: 2026
Condition: new
Binding: Paperback
Language: English
ISBN 10: 171850392X
ISBN 13: 9781718503922

About the Author

Giovanni Volpe is a professor in the Physics Department of the University of Gothenburg, Sweden, and head of the Soft Matter Lab. His research interests include deep learning, brain connectivity, statistical mechanics, and soft matter. He has authored more than 200 articles and reviews on these topics and has co-authored two books. He has also developed several software packages for microscopy, deep learning, and brain connectivity. Benjamin Midtvedt is a doctoral researcher working to enhance the field of microscopy through deep learning. The unifying focus of his research has been the development of accessible and practical AI optimized to the needs of the user. He has also been the lead developer of several Python-based open-source deep learning frameworks. Jesus Pineda is a doctoral researcher in physics focused on the intersection between deep learning and computer vision. He has co-authored several articles in high-impact journals on the application of deep learning to glean insights from microscopy data. Jesus is also a core developer of the deep learning software packages DeepTrack and Deeplay. Joana B. Pereira is an associate professor at Karolinska Institute in Sweden, where she focuses on investigating new biomarkers for neurodegenerative disorders, in particular Alzheimer's disease. Since 2020, she has organized an annual interdisciplinary conference called Emerging Topics in Artificial Intelligence in San Diego, CA. She is the scientific coordinator for NeurotechEU and winner of the 2021 de Leon Prize for best neuroimaging article in Alzheimer's disease. Carlo Manzo is an associate professor at the University of Vic, Spain, where he leads the Quantitative Bioimaging Lab. His research is dedicated to the analysis of biophysical processes, merging deep learning techniques with state-of-the-art imaging technologies to achieve single-molecule sensitivity. He is the founder of the Anomalous Diffusion challenge and winner of the 2017 E. Perez Paya Prize from the Sociedad de Biofisica de Espa¨a.

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