The Mathematical Engineering of Deep Learning
Benoit Liquet, Sarat Moka, and Yoni Nazarathy
▾ Chapters
Introduction 1 Supervised Machine Learning 2 Logistic Regression Type Neural Networks 3 Optimization Algorithms 4 General Fully Connected Neural Networks 5 Convolutional Neural Networks 6 Tricks of the Trade 7 Generative Adversarial Networks 8 Sequence Models 9 Deep Reinforcement Learning 10 Summary: Past, Present, and Future of Deep Learning Suggested Software Authors AMSI Summer School Course 2021 References

Authors

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