This repository contains code for a project to classify spam emails using a recurrent neural network (RNN). The project is divided into the following steps:
Data preparation
Model training
Model evaluation
The first step is to prepare the data. The data consists of a set of email messages, each of which is labeled as either spam or ham. The data is split into a training set and a test set.
The next step is to train the model. The model is an RNN that is trained to predict whether an email message is spam or ham. The model is trained using the training set.
The final step is to evaluate the model. The model is evaluated using the test set. The model's performance is measured using accuracy, precision, and recall.
To get started with this project, you will need to clone the repository to your local machine. You can do this using the following command:
git clone https://github.com/gokulakrishnanbalaji/Spam-classification-using-RNN.git
Now you are ready to start working on your project!
If you would like to contribute to this repository, please feel free to do so. You can submit pull requests for new features or bug fixes.
Contact If you have any questions or feedback, please feel free to contact me at [email protected].
I hope this helps!