Alternatives and similar repositories for DeepLearningPractice

Users that are interested in DeepLearningPractice are comparing it to the libraries listed below

• PatientEz / keras-attention-mechanism
  the extension of https://github.com/philipperemy/keras-attention-mechanism , create a new scipt to add attetion to input dimensions rath…
  ☆78Updated 10 months ago
• EthanChenYZ / Time-Series-Forecast
  Codes for time series forecast
  ☆146Updated 4 years ago
• mo2ye / SARIMA-LSTM
  建立SARIMA-LSTM混合模型预测时间序列问题。以PM2.5值为例，使用UCI公开的自2013年1月17日至2015年12月31日五大城市PM2.5小时检测数据，将数据按时间段划分，使用SARIMA过滤其线性趋势，再对过滤后的残差使用LSTM进行预测，最后对预测结果进行…
  ☆79Updated 6 years ago
• HiddenSharp / LSTM-SVM-RF-time-series
  Regression prediction of time series data using LSTM, SVM and random forest. 使用LSTM、SVM、随机森林对时间序列数据进行回归预测，注释拉满。
  ☆190Updated 5 years ago
• ChiYaoLa / TimeSeriesPredict
  used for Stock Prodiction&power prediction&Traffic prediction by ARIMA,xgboost,RNN,LSTM,TCN
  ☆111Updated 5 years ago
• yezhichen2 / cnn_lstm
  基于Keras的LSTM多变量时间序列预测
  ☆24Updated 7 years ago
• Corezcy / EEMD-LSTM-DO-Prediction
  EEMD、LSTM、time series prediction、DO、Deep Learning
  ☆88Updated 3 years ago
• PatientEz / LSTNet_Keras
  my blog https://blog.csdn.net/qq_35649669/article/details/105586099
  ☆47Updated 4 years ago
• Heitao5200 / LSTM-for-Time-Series-Forecasting-Pytorch
  使用LSTM、GRU、BPNN进行时间序列预测。Using LSTM\GRU\BPNN for time series forecasting. (Pytorch Edition)
  ☆57Updated 4 years ago
• WebLearning17 / SequencePrediction
  Pytorch 实现RNN、LSTM、GRU模型
  ☆79Updated 6 years ago
• lwb-xmu / Multivariate-multi-step-time-series-forecasting-via-LSTM
  多元多步时间序列的LSTM模型预测——基于Keras
  ☆80Updated 3 years ago
• tranducquy / tcn-fx-price-prediction
  Forex Time-Series Prediction Using TCN
  ☆44Updated 5 years ago
• PatientEz / Multidimensional-time-series-prediction-
  Multidimensional Time Series Prediction by using LSTM
  ☆56Updated 6 years ago
• ningmengwei-ata / Capacity-Forecast-with-TTE
  Undergradute final project with ARIMA,LSTM,GRU,Xgboost and DeepTTE.毕业论文代码库合集，包括基于ARIMA,LSTM,GRU进行时间序列预测，基于DeepTTE解决ETA(estimated time of …
  ☆20Updated 3 years ago
• EsmeYi / time-series-forcasting
  Using K-NN, SVM, Bayes, LSTM, and multi-variable LSTM models on time series forecasting
  ☆49Updated 5 years ago
• sksujan58 / Multivariate-time-series-forecasting-using-LSTM
  ☆250Updated last year
• Tuniverj / Pytorch-lstm-forecast
  基于pytorch搭建多特征LSTM时间序列预测
  ☆168Updated 2 years ago
• yuchengle / Arima
  利用时间序列预测汽车销量
  ☆40Updated 6 years ago
• zhangxu0307 / time-series-forecasting-keras
  time series forecasting using keras, inlcuding LSTM,RNN,MLP,GRU,SVR and multi-lag training and forecasting method, ICONIP2017 paper.
  ☆119Updated 6 years ago
• slydg / GRU_to_predict_timeseries
  使用pytorch搭建的循环神经网络在股票数据时间序列上的应用
  ☆105Updated 7 years ago
• koi-boy / CNN-LSTM-Attention
  CNN+LSTM+Attention predict stock
  ☆53Updated 3 years ago
• WhisperRen / TPA-LSTM_in_tf2
  Implementation of TPA-LSTM in TensorFlow2
  ☆17Updated 3 years ago
• lu-zhao / EMD_LSTM
  ☆32Updated 5 years ago
• RuifMaxx / Multidimensional-time-series-with-transformer
  transformer/self-attention for Multidimensional time series forecasting 使用transformer架构实现多维时间预测
  ☆234Updated last year
• momodagithub / regression-prediction-algorithms
  使用支持向量机、弹性网络、随机森林、LSTM、SARIMA等多种算法进行时间序列的回归预测，除此以外还采取了多种组合方法对以上算法输出的结果进行组合预测。Support vector machine, elastic network, random forest, LSTM…
  ☆46Updated 4 years ago
• sarikayamehmet / cnn-bilstm-attention
  Multivariate Time Series Prediction using Keras (CNN BiLSTM Attention)
  ☆91Updated 4 years ago
• yangwohenmai / TimeSeriesForecasting
  基于统计学的时间序列预测(AR,ARM).
  ☆276Updated 4 years ago
• wqk666999 / CNN-LSTM-Attention
  使用卷积神经网络-长短期记忆网络（bi-LSTM）-注意力机制对股票收盘价进行回归预测。The convolution neural network, short-term memory network and attention mechanism are used to…
  ☆279Updated last year
• iwuqing / Time-Series-Classification-based-on-KNN
  基于KNN聚类算法结合Dynamic Time Warping（动态时间调整）的时间序列分类
  ☆61Updated 5 years ago
• currylym / time-series-prediction-learning-record
  Learning Record about TSP
  ☆58Updated 6 years ago