Neural networks have been the come-back kids of machine learning. They were invented in the 80s, but surged back into the limelight in the late 90s to become a powerful tool at the heart of deep learning. This video describes what neural networks are, how they work in materials informatics,
Check out the whole materials informatics series at with workbooks and course notes available at
0:00 How do artificial neural networks differ from biological analogues
4:15 basic elements of a vanilla neural networks
7:39 notation used in neural networks
12:33 activation functions
14:08 how do neural nets learn?
16:05 concept behind backpropagation
19:20 stochastic gradient descent and learning curves
22:40 math of backpropagation
29:12 tuning neural network hyperparameters
34:47 walkthrough of pytorch notebook for neural network
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