Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
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Updated
Mar 15, 2023 - Jupyter Notebook
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
In PyTorch Learing Neural Networks Likes CNN、BiLSTM
Predict Cryptocurrency Price with Deep Learning
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
Neural Machine Translation with Keras
百度云魅族深度学习应用大赛
Keras tutorial for beginners (using TF backend)
Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).
Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models
Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
Haste: a fast, simple, and open RNN library
ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @udacity.
RNN and general weights, gradients, & activations visualization in Keras & TensorFlow
Porting of Skip-Thoughts pretrained models from Theano to PyTorch & Torch7
A Keras library for multi-step time-series forecasting.
Word Embedding + LSTM + FC
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