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PyTorch Tutorial for Deep Learning Researchers
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.
Build your neural network easy and fast, 莫烦Python中文教学
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
Tensorflow tutorial from basic to hard
Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
Sequence modeling benchmarks and temporal convolutional networks
Text Classification Cnn Rnn
Bert Chinese Text Classification Pytorch
Simple and comprehensive tutorials in TensorFlow
Differentiable architecture search for convolutional and recurrent networks
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
Handwriting Synthesis with RNNs ✏️
Char Rnn Tensorflow
Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow
Deep learning driven jazz generation using Keras & Theano!
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.
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Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)
Datasets, tools, and benchmarks for representation learning of code.
Deep Learning Time Series
List of papers, code and experiments using deep learning for time series forecasting
PyTorch 官方中文教程包含 60 分钟快速入门教程，强化教程，计算机视觉，自然语言处理，生成对抗网络，强化学习。欢迎 Star，Fork！
Handwritten Text Recognition (HTR) system implemented with TensorFlow.
Text Classification Algorithms: A Survey
Keras Temporal Convolutional Network.
Top Deep Learning
Top 200 deep learning Github repositories sorted by the number of stars.
Data augmentation for NLP, presented at EMNLP 2019
This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
Machine Learning Experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
End To End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
Word Rnn Tensorflow
Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.
Deep Learning With Pytorch Tutorials
Machine Learning Curriculum
💻 Learn to make machines learn so that you don't have to struggle to program them; The ultimate list
Seq2seq Signal Prediction
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
Text classifier for Hierarchical Attention Networks for Document Classification
TextBox 2.0 is a text generation library with pre-trained language models
1st Place Solution for Zhihu Machine Learning Challenge . Implementation of various text-classification models.(知乎看山杯第一名解决方案)
Char Rnn Tensorflow
Multi-language Char RNN for TensorFlow >= 1.2.
Chatbot in 200 lines of code using TensorLayer
Rnn Time Series Anomaly Detection
RNN based Time-series Anomaly detector model implemented in Pytorch.
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Multilayer LSTM and Mixture Density Network for modelling path-level SVG Vector Graphics data in TensorFlow
Tf Rnn Attention
Tensorflow implementation of attention mechanism for text classification tasks.
Music Source Separation
Deep neural networks for separating singing voice from music written in TensorFlow
Time Series Prediction
Time series deep learning models in TensorFlow-TFTS
Visualizing RNNs using the attention mechanism
Sequence to Sequence Models with PyTorch
CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017
A lightweight, simple-to-use, RNN wake word listener
Cs224n Learning Camp
Machine Learning on Sequential Data Using a Recurrent Weighted Average
CRF-RNN Keras/Tensorflow version
RNN-based generative models for speech.
WTTE-RNN a framework for churn and time to event prediction
Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.
Tensorflow Vae Gan Draw
A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
Multi Class Text Classification Cnn Rnn
Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.
Text Classification Pytorch
Text classification using deep learning models in Pytorch
A bidirectional recurrent neural network model with attention mechanism for restoring missing punctuation in unsegmented text
Named Entity Recognition using multilayered bidirectional LSTM
TensorFlow implementation of Independently Recurrent Neural Networks
Tensorflow Rnn Shakespeare
Code from the "Tensorflow and deep learning - without a PhD, Part 2" session on Recurrent Neural Networks.
Deep Trading Agent
Deep Reinforcement Learning based Trading Agent for Bitcoin
Pixel Rnn Tensorflow
Closed-form Continuous-time Neural Networks
Text Classification Models Tf
Tensorflow implementations of Text Classification Models.
A curated list of Best Artificial Intelligence Resources
End-to-end ASR/LM implementation with PyTorch
A TensorFlow implementation of Recurrent Neural Networks for Sequence Classification and Sequence Labeling
Trending Deep Learning
Top 100 trending deep learning repositories sorted by the number of stars gained on a specific day.
Keras Layer implementation of Attention for Sequential models
Stock Price Prediction Lstm
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network
Rnn Tutorial Gru Lstm
Language Model GRU with Python and Theano
Tensorflow Char Rnn
Char-RNN implemented using TensorFlow.
RNN for Spoken Language Understanding
Text Classification Library in Keras
Reinforcement Learning for Portfolio Management
Recurrent (conditional) generative adversarial networks for generating real-valued time series data.
Instacart Basket Prediction
Kaggle | Instacart Market Basket Analysis🥕🥉
RMDL: Random Multimodel Deep Learning for Classification
Stock price prediction with LSTMs in TensorFlow
auto-tuning momentum SGD optimizer
Emotion Recognition Using Speech
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
Tensorflow Convlstm Cell
A ConvLSTM cell with layer normalization and peepholes for TensorFlow's RNN API.
Simple RNN, LSTM and Differentiable Neural Computer in pure Numpy
Generative adversarial networks (GAN) applied to sequential data via recurrent neural networks (RNN).
First Steps Towards Deep Learning
This is an open sourced book on deep learning.
Demonstration of recurrent neural network implemented with Theano
Timeseries Clustering Vae
Variational Recurrent Autoencoder for timeseries clustering in pytorch
Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP
C Rnn Gan
Implementation of C-RNN-GAN.
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