frank-lee5's Stars
nilaoda/N_m3u8DL-CLI
[.NET] m3u8 downloader 开源的命令行m3u8/HLS/dash下载器，支持普通AES-128-CBC解密，多线程，自定义请求头等. 支持简体中文,繁体中文和英文. English Supported.
datawhalechina/leedl-tutorial
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
rcmaehl/WhyNotWin11
Detection Script to help identify why your PC is not Windows 11 Release Ready. Now Supporting Update Checks!
jaungiers/LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
VeritasYin/STGCN_IJCAI-18
[IJCAI'18] Spatio-Temporal Graph Convolutional Networks
hichenway/stock_predict_with_LSTM
Predict stock with LSTM supporting pytorch, keras and tensorflow
Davidham3/STSGCN
AAAI 2020. Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting
jsyoon0823/Time-series-prediction
Basic RNN, LSTM, GRU, and Attention for time-series prediction
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.
LitoNeo/pytorch-AutoEncoders
Autoencoders in PyTorch
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
StephenZheng0315/PM2.5-Prediction-Based-on-Random-Forest-Algorithm
vikmreddy/deep-air
Predicting Air Pollution in Beijing, China using Deep Neural Nets
EsmeYi/time-series-forcasting
Using K-NN, SVM, Bayes, LSTM, and multi-variable LSTM models on time series forecasting
grtvishnu/Air-Pollution-Prediction-and-Forecasting
:octocat: Detection and Prediction of Air quality Index :octocat:
gabrielloye/GRU_Prediction
lu-zhao/EMD_LSTM
PatientEz/lstm-time-series-forecasting_keras
lstm time series forecasting implemented by keras 2.4 & tensorflow 2.3
Bmajor98/emd
Python implementations of empirical mode decomposition as well as EEMD and CEEMD variants.
Dieselmarble/Beijing-PM2.5-Forecasting
Prediction of Beijing PM2.5 using classic machine learning methods
k3dves/Foreign-exchange-rates-forecasting
Foreign exchange rates forecasting using EMD with LSTM
prince381/air-pollution
Predicting the amount of Particulate Matter (PM2.5) content in the air
S16201512/PM2.5-Prediction
李宏毅机器学习中的PM2.5预测的实现
Suzzanemansi/EMD-LSTM-MLP
To increase the prediction accuracy by using EMD with LSTM an MLP networks.
kqhuynguyen/gcn-japan-weather-forecast
Forecasting task. Predicting temperatures from sensors data.
shubhammittal009/air-pollution_prediction
air-pollution prediction using multivariate regression with python
stefanie17/PM2.5-Prediction-Based-on-Interactive-Multiple-Machine-Learning-Models
In this project, different machine learning method including SVM, decision tree, random forest, neural network and Xgboost are used to make a prediction of PM2.5. Xgboost shows the highest accuracy and SVM has the lowest accuracy for predictions. Subset sample deletion was used to improve performance for it and increased the accuracy ~12%. Bagged decision tree, random forest and extra trees were compared and exhibited higher accuracy comparing with decision tree on prediction of PM2.5. Stacking was also used to reduce the bias and irrelevant features by combining other models’ predictions. SVM, decision tree, random forest, Xgboost were used as the first layer models. Xgboost shows the best performance as the second layer model comparing with the other three classification models.
bbjornstad/air-pollution-prediction
My project on time-series analysis and future prediction of levels of air pollution in the US
AviralPamecha/AutoEncoders
Dimensionality Reduction Through Autoencoders
Sud0302/Air-Pollution-Prediction