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The math behind
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Classroom Contents
Recurrent Neural Networks Explained Easily
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- 1 Intro
- 2 Univariate time series
- 3 Multivariate time series
- 4 Intuition
- 5 RNN architecture
- 6 Unrolling a recurrent layer
- 7 Data shape
- 8 Sequence to vector RNN
- 9 Sequence to sequence RNN
- 10 Memory cell for simple RNN
- 11 Why do we use tanh?
- 12 Backpropagation through time (BPTT)
- 13 The math behind
- 14 Issues with simple RNNS
- 15 What's up next?
