Climate change has a huge impact on global food production and food security. Extreme weathers can have significant impacts on crops. Hence, modelling can be a useful tool to help various stakeholders mitigate these devastating risks.

What it does

Our model takes in Enhanced Vegetation Index (EVI) values, temperatures values throughout the years and crop yields from previous years to predict the crop yield in the current year.

How we built it

We used pandas for exploratory data analysis and Tensorflow Keras to build our model. We experimented with different recurrent neural network (RNNs) and Convolutional Neural Network Architecture for our model.

Challenges we ran into

Underfitting and overfitting the model

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