Deep Learning¶

References¶

• Deep Learning | Dr. Tamizharasan

• Andrej Karpathy

• The spelled-out intro to neural networks and backpropagation: building micrograd | Andrej Karpathy

• Deep Learning - Deep Understanding | Mike x Cohen

• MIT 6.S191: Introduction to Deep Learning

• Deep Learning in Life Sciences | MIT

• Deep Learning for Physicists | Florian Marquardt

• Deep Learning Crash Course | Leo Isikdogan

• Intro to Deep Learning | CMU

• Deep Learning Systems: Algorithms and Implementation | CMU

• Stanford

• Deep Learning Coursera | Andrew Ng

• Deep Learning | Stanford CS230

• Deep Learning | VU University Amsterdam

• Maziar Raissi | Applied Deep Learning

• Applied Deep Learning 2023 | TU Wien

• Deep Learning | Tübingen Machine Learning | Andreas Geiger, 2023

• Deep Learning | IIT Madras

• New

• Old

  • Part 1
  • Part 2

• Deep Learning Concepts (Simply Explained) | Pedram Jahangiry

• Deep Learning for Economics (Spring 2023) | Harvard

• Unleashing Novel Data at Scale | Harvard

• Neural Networks for Machine Learning — Geoffrey Hinton, UofT

• CS 152: Neural Networks/Deep Learning—Spring, 2021 | Neil Rhodes

• Deep Learning for Autonomous Vehicles | MIT

• Local Explanations for Deep Learning Models

• Deep Learning (STAT 940) , Fall 2023 | University of Waterloo

• Deep Learning - F2023 University of Guelph

• Foundations of Deep Learning | Soheil Feizi | University of Maryland

• Deep Unsupervised Learning | UC Berkeley

• Deep Learning | Se Young Yun

• Geometric Deep Learning | Michael Bronstein | Oxford

• Transformers United | Stanford

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