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Sequence Modelling and NLP With Deep Learning (Keras)

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Tim Scarfe takes you on a whirlwind tour of sequence modelling in deep learning using Keras! • Intro • Outline 2:03 • What is a neural network 2:38 • Concepts of deep learning 3:32 • What is a sequence? 8:34 • What is sequence processing? 9:28 • Tokenization 10:35 • word vectors vs word embeddings 12:06 • More about word embeddings 13:26 • Recurrent neural networks (RNNs) 15:26 • LSTMs 17:04 • GRUs vs LSTMs 18:31 • Bi-directional RNNs 19:28 • 1d CNNs and tour of convolutional filtering in MATLAB 20:22 • Stacking RNNs+CNNs 25:42 • Universal machine learning process 25:56 • Demo-1 hot encoding 29:17 • Demo-Defining RNNs in Keras 31:17 • Demo-IMDB in Keras 32:30 • Performance/scoring/eval of deep learning models 35:40 • Question on material and sigmoid activation 38:39 • Temperature forecasting problem (cover GRU, LSTM, regularisation, bidirectional, stacking) 41:55 • 1D CNNs 49.49 • Questions 52:00 Slides; https://github.com/ecsplendid/deep-learning-sequences-talk/blob/master/talk.pdf Make sure you buy yourself a copy of Francois Chollet's book https://www.manning.com/books/deep-learning-with-python
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Text Comments (5)
Ömer Yalçın (1 month ago)
Hi that is great video , thanks for sharing. You can use "keras.layers.CuDNNLSTM()" for uping speed.
Saravana Kumar (1 month ago)
Are you British
Dinesh Mane (4 months ago)
Fantastic session Tim, and content is really good. You have explained return_sequence = True parameter with two examples which helped me to understand clearly. Thanks for sharing the video :)
awesome video sir. i will read the book.

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