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Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
 

Inside Deep Learning: theory and practice of modern deep learning

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  • 2. Deep learning isn’t just for big tech companies and academics. Anyone who needs to find meaningful insights and patterns in their data can benefit from these practical techniques! The unique ability for your systems to learn by example makes deep learning widely applicable across industries and use-cases, from filtering out spam to driving cars.
  • 3. Inside Deep Learning is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped—you’ll dive into math, theory, and practical applications. Everything is clearly explained in plain language.
  • 4. Inside Deep Learning is a fast-paced beginners guide to solving common technical problems with deep learning. Written for everyday developers, without complex mathematical proofs or dense academic theory. You’ll learn how deep learning works through clear explanations, annotated code and equations as you work through dozens of instantly useful PyTorch examples. Best of all, every deep learning solution in this book can run in less than fifteen minutes using free GPU hardware!
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  • 6. About the author: Edward Raff is a Chief Scientist at Booz Allen Hamilton, and the author of the JSAT machine learning library. His research includes deep learning, malware detection, reproducibility in ML, fairness/bias, and high performance computing. He is also a visiting professor at the University of Maryland, Baltimore County and teaches deep learning in the Data Science department. Dr. Raff has over 40 peer reviewed publications, three best paper awards, and has presented at numerous major conferences.
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