Introduction to Deep Learning - Ruiz, Mauricio Alberto Ortega
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Delve into deep learning fundamentals where theory meets practice. Explore neural networks, convolutional and recurrent architectures, and deep reinforcement learning. Hands-on exercises and examples illuminate model training and innovative problem-solving across diverse fields.

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Produktbeschreibung
Delve into deep learning fundamentals where theory meets practice. Explore neural networks, convolutional and recurrent architectures, and deep reinforcement learning. Hands-on exercises and examples illuminate model training and innovative problem-solving across diverse fields.
Autorenporträt
Mauricio Alberto Ortega-Ruíz is an Electrical Engineering graduate from UNAM at Mexico, with experience in technical support for electronics equipment, field service and training services. This experience accomplishes instrumentation equipment, photo-lab and automation industry. Mauricio's academic journey includes a M. Sc. in signal processing at the Imperial College of Science Technology and Medicine and a PhD at City University of London, both are UK Universities. His main Research interest is in AI applications for medical imaging analysis and particularly in digital histopathology for breast cancer grading, he has published Scientific papers on this topic and participated in the Automated Gleason Grand Challenge 2022 in which he developed Deep Learning methods for Prostate cancer image grading and obtained the 10th place in the final ranking. He is cofounder of DigPatho, a research group for the LATAM region. Besides his passion for Research in the medical image field he has also demonstrated interest in signal processing, and other imaging applications. He dedicates time to culture and music, and as an amateur violist, he was member of the Imperial College Chamber orchestra during his masters.