LSTM (Long Short-Term Memory) is a type of Recurrent Neural Network (RNN) architecture designed to efficiently capture and utilize long-term dependencies in sequential data. In this project, I will be developping an LSTM model to predict future CO2 emission.

CO2 emission data is a Timeseries dataset, which fits for sequential model perfectly.

I will be using CO2 emission data set by country from Kaggle.

• TensorFlow
• Keras
• LSTM
• Sequential Model

I have used TensorFlow framework for this project.

pip install tensorflow

1. Long Short-Term Memory model (LSTM)
2. Saving weights as checkpoints in Keras

Try it on my profile