This project is a chatbot developed from scratch using Python and TensorFlow. The chatbot is designed to interact with users and provide intelligent responses to their inputs. It utilizes a sequence-to-sequence model based on Long Short-Term Memory (LSTM) architecture to achieve accurate and engaging interactions.
See it in my blog.
The main goal of this project is to create an AI-powered chatbot capable of understanding natural language inputs and generating contextually relevant responses. Using LSTM-based sequence-to-sequence models, the chatbot can retain important information over extended sequences, leading to more coherent and meaningful user interactions.
- Natural Language Processing: The chatbot can understand and process natural language inputs from users.
- LSTM-based Model: The chatbot's core architecture is based on LSTM-based sequence-to-sequence models for effective information retention.
- Engaging Interactions: The chatbot generates contextually appropriate responses, making the conversations with users more engaging.
- Python and TensorFlow: The project is implemented in Python using the TensorFlow framework for efficient machine learning computations.
To get started with the chatbot, follow the steps below:
- Clone the repository to your local machine.
- Install the required dependencies (see Dependencies).
- Train the chatbot on a dataset of your choice or utilize the pre-trained model.
- Run the chatbot and start interacting!
Make sure you have the following dependencies installed:
- Python 3.7+
- TensorFlow 2.x
- NumPy
- Pandas
- Scikit-learn
- Matplotlib
The chatbot will start interacting with you, responding to your inputs based on the trained model.
Contributions to this project are welcome! Feel free to submit issues or pull requests if you have any ideas for improvement.
This project is licensed under the MIT License. You are free to modify and distribute the code as per the terms of the license.
Enjoy chatting with the chatbot! 🤖