Deep Learning¶

References¶

• Deep Learning | Dr. Tamizharasan
• Neural Networks: Zero to Hero | Andrej Karpathy
• Deep Learning for Computer Vision | Andrej Karpathy | Stanford
• 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
• Deep Learning | Islem Rekik, Basira Lab | Imperial College London
• Deep Graph Learning | Islem Rekik, Basira Lab | Imperial College London
• Transformers United | Stanford
• Neural Networks | Hugo Larochelle | Université de Sherbrooke
• Neural Networks | Meerkat Statistics
• Deep Learning Fundamentals | Lightning.ai
• Deep Learning | École polytechnique
• Deep Learning UC Berkeley
• Deep Learning | TUM

Comments