Bidirectional RNN | Deep Learning | In-depth Explanation & Equations
Bidirectional RNN provides greater accuracy in prediction and is a powerful model in Deep Learning when dealing with sequence data. Limitation of uni-directional RNN is that it makes the prediction using only the information that has been seen previously to that point. But Bidirectional RNN makes the prediction by scanning the input from both the directions.
Bidirectional RNN is a bit more complex version of uni-directional RNN and can be used along with Simple RNN, GRU or LSTM. In this video we have covered the in-depth working of Bidirectional RNN along with equations.
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Timestamps:
0:00 Intro
0:28 Limitations of RNN
2:02 Bidirectional RNN
4:18 Visualising Bidirectional RNN
6:38 Limitations of Bidirectional RNN
7:08 Outro
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Chapters (6)
Intro
0:28
Limitations of RNN
2:02
Bidirectional RNN
4:18
Visualising Bidirectional RNN
6:38
Limitations of Bidirectional RNN
7:08
Outro
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Tutor Explanation
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