wenyawilla,github

100-days-of-ml-code

100-Days-Of-ML-Code中文版

100-days-of-ml-code-1

100 Days of ML Coding

an-attention-based-spatiotemporal-lstm-network-for-next-poi-recommendation

A python vision code of An Attention-based Spatiotemporal LSTM Network for Next POI Recommendation

at-conv-lstm

A Hybrid Deep Learning Model with Attention based ConvLSTM Networks for Short-Term Traffic Flow Prediction

attention-based-bilstm-relation-extraction

Tensorflow Implementation of "Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification" (ACL 2016)

attention-based-lstm-a-machine-leanring-approach-for-automatic-sleep-stages-classification

Paper of "Attention-based LSTM: A Machine Leanring Approach for Automatic Sleep Stages Classification", in preparation for the IEEE TRANSACTIONS ON AFFECTIVE COMPUTING.

attention-clx-stock-prediction

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction

bridgechange

R package for regularization and change-point analysis in time series and panel data using Bayesian inference

causal_inference_python_code

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

causalot

:exclamation: This is a read-only mirror of the CRAN R package repository. causalOT — Optimal Transport Weights for Causal Inference

cbipm

[ICML2023] Official code for "Covariate balancing using the integral probability metric for causal inference"

convolutional_lstm_pytorch

Multi-layer convolutional LSTM with Pytorch

counterfactual-estimation-optimal-transport

Counterfactual Estimation using Optimal Transport: A Causal Inference Approach

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

dagpr

paper

ea-lstm

EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction

hd-causal-effect

Learning high-dimensional causal effect with deep models

lstm

基于LSTM的时间序列预测研究

lstm-attention

Attention-based bidirectional LSTM for Classification Task (ICASSP)

lstm-attention-frauddetection

Enhanced Credit Card Fraud Detection based on Attention mechanism and LSTM deep Model, the output of LSTM is the input of attention.

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

lstm_attention

attention-based LSTM/Dense implemented by Keras

lstm_rnn_tutorials_with_demo

LSTM-RNN Tutorial with LSTM and RNN Tutorial with Demo with Demo Projects such as Stock/Bitcoin Time Series Prediction, Sentiment Analysis, Music Generation using Keras-Tensorflow