LLM Chronicles #4.6: Building an Encoder/Decoder RNN in PyTorch to Translate from English to Italian скачать в хорошем качестве

LLM Chronicles #4.6: Building an Encoder/Decoder RNN in PyTorch to Translate from English to Italian

In this lab we'll use PyTorch to build a encoder/decoder RNN for language translation, similar to the model described in the 2014 paper "Sequence to Sequence Learning with Neural Networks” by OpenAI's chief scientist Ilya Sutskever. Our RNN layers will use LSTM (Long Short-Term Memory) cells. 🖹 Lab Notebook: https://colab.research.google.com/dri... 🕤 Timestamps: 00:10 - Sutskever's Paper on Language Translation with RNNs 00:27 - Loading the Dataset, Tokenizer and Vocabulary 02:40 - PyTorch Dataset and DataLoader Objects 05:20 - Encoder / Decoder RNN in PyTorch 08:15 - Inference / Forward Pass for Translation 10:10 - Training Loop, Teacher Forcing 15:54 - Using/Evaluating the Trained Model 19:15 - Bi-Directional RNN for the Encoder 22:10 - Using/Evaluating the Trained Bi-Directional RNN 23:29 - Comparing our model to Sutskever's Paper References: "Sequence to Sequence Learning with Neural Networks", https://arxiv.org/abs/1409.3215 Don't forget to like, share, and subscribe for more neural network adventures!