Multivariate Time-Series Forecasting with LSTM and Attention Mechanism - SJSU (2021): Used Python and TensorFlow package to predict the remaining useful life of Turbofan engine applying LSTM and Attention Mechanism in an Encoder-Decoder architecture.

Demonstration of Multivariate Time Series Forecasting (Household Electric Power Consumption Dataset)--Long Short-Term Memory (LSTM) Network ) -- Preprocessing/Exploratory -- Keras Time Series Generator

This is a python nb in which I have practiced univariate and multivariate Time Series Forecasting using CNN-LSTM

Predicts Walgreens (WBA) stock prices using LSTM deep learning. Implements multivariate time series forecasting with historical stock data to analyze trends and make future price predictions. Built with Python, TensorFlow, and Keras.

Built a multivariate LSTM model in Python to forecast air pollution using time series data. Preprocessed data with lag features, normalized inputs, and reshaped for supervised learning. Trained on multiple timesteps, evaluated with RMSE & MAE, and delivered a scalable forecasting pipeline.