lstm-attention

A PyTorch Tutorials of Sentiment Analysis Classification (RNN, LSTM, Bi-LSTM, LSTM+Attention, CNN)

Building Time series forecasting models, including the XGboost Regressor, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), CNN-LSTM, and LSTM-Attention. Additionally, hybrid models like GRU-XGBoost and LSTM-Attention-XGBoost for Electricity Demand and price prediction

Tencent Advertisement Algorithm Competition 2020 / 2020 腾讯广告算法大赛 TOP12

In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity fo…

pytorch实现的基于attention is all your need提出的Q,K,V的attention模板和派生的attention实现。

Neural Persian Poet: A sequence-to-sequence model for composing Persian poetry

sentiment-analysis,document-classification,svm,logistic-regression,rcnn-text-classification, cnn-text-classification, lstm-text-classification, naive-bayes-classifier, sklearn-classify, pytorch

Time Series Classification models: (1) bidirectional LSTM, (2) LSTM with temporal pooling, (3) LSTM with attention, (4) TCN

read/write on a memory array

An AI robotic project on posture recognition.

Sentiment Analysis of Restaurant Reviews to Enhance Customer Experience and Optimize Operations

Three AI models for translating French to Portuguese.

Enhanced electricity price forecasting with leak-free preprocessing, temporal feature engineering, baseline models, LSTM-Attention, and extended error analysis.

Optimizing Sentiment Analysis Models for Accurate Predictions

A framework for the comparative training and evaluation of statistical and deep learning models for multi-feature categorical sequence modeling, utilizing feature fusion and automated with MLflow and Optuna integration.

📈 Generate accurate demand forecasts with Python using synthetic data, featuring ARIMA/SARIMA modeling, evaluation metrics, and reproducible visualizations.