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Applications of Deep Neural Networks - 2016 Version

Jeff Heaton via YouTube

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Explore deep learning fundamentals through recorded classroom sessions from Washington University's Applications of Deep Neural Networks course. Dive into comprehensive coverage of neural network architectures, implementation techniques, and real-world applications across 14 structured class sessions totaling over 23 hours of instruction. Learn from in-class recordings that capture the interactive learning environment, including student questions and instructor explanations that provide deeper insights into complex concepts. Master essential deep learning principles including network design, training methodologies, optimization techniques, and practical deployment strategies. Gain hands-on understanding of how neural networks solve problems across various domains through detailed examples and case studies presented in an academic setting. Note that this represents the 2016 version of the curriculum, with updated materials available through the instructor's current course offerings.

Syllabus

Applications of Deep Neural Networks Class Session 1
Applications of Deep Neural Networks Class Session 2
Applications of Deep Neural Networks Class Session 3
Applications of Deep Neural Networks Class Session 4
Applications of Deep Neural Networks Class Session 5
Applications of Deep Neural Networks Class Session 6
Applications of Deep Neural Networks Class Session 7
Applications of Deep Neural Networks Class Session 8
Applications of Deep Neural Networks Class Session 9
Applications of Deep Neural Networks Class Session 10
Applications of Deep Neural Networks Class Session 11
Applications of Deep Neural Networks Class Session 12
Applications of Deep Neural Networks Class Session 13
Applications of Deep Neural Networks Class Session 14