DeepLearning1.1, Gradient Descent Methods for Artificial Neural Networks (Introduction)
From Wulfram Gerstner
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- Architecture - AR
- Euler courses
- Life sciences - BIO
- Life Sciences Engineering - BIOENG
- Chemistry - CH
- Chemical engineering - ChE
- Civil engineering - CIVIL
- Communication Systems - COM
- Computer Science - CS
- Digital Humanities - DH
- Electrical Engineering - EE
- Engineering - ENG
- Environmental Sciences and Engineering - ENV
- Finance - FIN
- Humanities - HUM
- Quantum sciences and engineering - QUANT
- Materials Science and Engineering - MA
- Mathematics - MATH
- Mechanical Engineering - ME
- Management Technology and Entrepreneurship - MGT
- Microengineering and microsystems - MICRO
- Materials Science and Engineering - MSE
- Neuro-x - NX
- Design Together - PENS
- Preparatory Year - PREPA
- Physics - PHYS
- EPFL miscellaneous
- Mediaspace@EPFL
- Kaltura Help
- Ask for a channel to add videos
- Live courses recordings
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