Recurrent Neural Networks - Understanding RNNs! - GRU | LSTM | BPTT & Code Example!
Chapter 10 - Recurrent Neural Networks! In this chapter we will learn about RNNs as the baseline for Natural Language Processing with deep neural networks. We will discuss how it works, advanced architectures as GRU and LSTM. Multilayer RNNs, Bidirectional RNNs and code example. Parts: 00:00-03:33- Sequential Data Processing 03:33-04:07 - RNN Architecture 04:07-06:16 - Back Propagation Through Time (BPTT) 06:16-06:55 - The Vanishing Gradients Problem 06:55-08:54 - Gated Recurrent Unit (GRU) 08:54-10:12 - Long Short-Term Memory (LSTM) 10:12-11:02 - Multilayered RNN 11:02-12:15 - Bi-Directional RNN 12:15-19:46 - Code Example You can find the notebook in the video in the following link: https://github.com/HallOfNN-CodeFacto... Please feel free to leave comments and ask everything! #deeplearning #recurrentneuralnetowrks #artificialneuralnetwork #machinelearning #regularization #artificialintelligence #deeplearning #education #nlp #multilayered #perceptron #recurrent #gru #lstm #bidirectional #codeexamples
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