搜索资源列表
LSTM.tar
- C-package of "Long Short-Term Memory" for Protein classification
rnnlib.tar
- RNNLIB可以用来做语音识别、手写字符识别。由大牛Alex Graves编写，专门做RNN、LSTM的研究。他的主页是http://www.cs.toronto.edu/~graves/-RNNLIB is a recurrent neural network library for sequence labelling problems, such as speech and handwriting recognition.
CWS_LSTM-master
- 一款基于LSTM的中文分词工具包！很支持！-A LSTM based Chinese word Kit! Very supportive!
DL4J_LSTM
- deeplearning4j依赖下，Java实现神经网络LSTM算法，DailyData.class实现数据结构，StockDataIterator.class进行数据预处理-deeplearning4j dependent under, Java LSTM realize neural network algorithm, DailyData.class data structure, StockDataIterator.class
char-rnn-master
- 此代碼實現多層遞歸神經網絡（RNN，LSTM和GRU）從字符級語言模型訓練/採樣。換句話說，模型採用一個文本文件作為輸入和火車一個遞歸神經網絡的學習來預測下一個字符的序列。-This code implements multi-layer Recurrent Neural Network (RNN, LSTM, and GRU) for training/sampling character-level language models
ChineseNER-master
- Pyhton实现biLSTM+CRF算法,应用于中文命名实体识别(Pyhton implementation of biLSTM+CRF algorithm, applied to Chinese named entity recognition)
LSTM
- 神经网络 matlab 的一个样例；Neural network matlab a sample(Neural network matlab a sample)
deeplearningbook-chinese-0.5-beta
- 卷积神经网络、循环神经网络、递归神经网络、深度信念网络、深度堆叠网络、LSTM长短时记忆(Convolution neural network, circulating neural network, recursive neural network, deep belief network, deep stack network, LSTM length memory)
RerankNER-master
- 这份代码是基于深度神经网络的英文命名实体识别，主要算法是LSTM+CRF(This code is based on deep neural network English named entity recognition LSTM+CRF)
RNN_2015
- RNN 论文阅读，帮助理解RNN的实现，以及应用。涉及lstm等rnn网络(RNN papers; including lstm)
keras-master (1)
- Keras 示例代码，包括CNN，LSTM，CNN-LSTM等，非常全面。(Keras sample code, including CNN, LSTM, CNN-LSTM, and so on, is very comprehensive.)
Seq2Seq
- 自然语言处理中 Seq2Seq LSTM搭建示例(This is the code of Seq2Seq model in NLP,using LSTM neural network)
time
- 时序预测，预测下一个月乘客数量。采用lstm神经网络来预测(Time series prediction)
JRNN-master
- java语音编写的lstm学习，可以实现文本学习(Java speech writing LSTM learning, can achieve text learning)
nn_code
- 使用Python实现的一些简单神经网络算法，实现的神经网络包括BP,CNN,RNN,LSTM等，主要是理解这些神经网络的算法原理，并附有mnist数字识别例子。(neural network,include BP,CNN,RNN,LSTM.)
main
- NLP-NER的一个简单Demo。模型基于LSTM-CRF(A Demon for Chinese-NER from https://github.com/zjy-ucas/ChineseNER)
data
- 训练NER的语料文件，已全文标注，四个字段(Training NER's corpus file, full text annotation, four fields)
LSTMshili
- 做预测,预测股票趋势的一个小例子，可运行，比较简单明了，容易理解，适合初学者(A small example of forecasting, predicting stock trends, running, easy to understand, easy to understand, suitable for beginners)
tensorflow-convlstm-cell-master
- Tensorflow实现LSTM，Python代码用命令行安装setup文件(Tensorflow implements LSTM, Python code installs setup file with command line)
hybrid-ARIMA-LSTM-model-master
- 使用LSTM-ARIMA模型进行混合预测，ARIMA做线性部分的预测，LSTM做非线性部分(LSTM-ARIMA model is used for mixed prediction, ARIMA for linear prediction and LSTM for nonlinear prediction)