Multiple Imputation with LightGBM in Python

LSTM-XGBoost Time Series Forecasting

Materials for an online-course - "Practical XGBoost in Python"

Tutorial how to use xgboost

Electricity price (energy demand) forecasting using different ML, DL, stacked DL and hybrid methods (XGBoost, GRU, LSTM, CNN, CNN-LSTM, LSTM-Attention, Hybrid GRU-XGBoost and Hybrid LSTM-Attention-…

CNN-BiGRU-Attention模型

Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

Tutorial on survival analysis using TensorFlow.

This Python function dm_test implements the Diebold-Mariano Test (1995) to statistically test forecast accuracy equivalence for 2 sets of predictions with modification suggested by Harvey et. al (1…

Sequence modeling benchmarks and temporal convolutional networks

CSDN中的代码 在github中建立仓库存储

CEEMDAN_LSTM is a Python project for decomposition-integration forecasting models based on EMD methods and LSTM.

Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow

In PyTorch Learing Neural Networks Likes CNN、BiLSTM

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

Repo for the Deep Learning Nanodegree Foundations program.

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

Learning about and doing projects with recurrent neural networks