This repository contains the documentation and code for a mini project assigned to sixth-semester students as part of the requirements for the Bachelor of Technology in Computer Science and Engineering degree at Graphic Era (Deemed to be University), Dehradun.
In the ever-advancing realm of technology, there is an escalating demand for innovative solutions across various sectors, including health, finance, entertainment, and the music industry. In today's digital age, music streaming platforms have gained immense popularity, granting users access to an extensive collection of songs. Concurrently, chatbots, powered by Artificial Intelligence (AI), have emerged as vital applications designed to simulate human-like interactions and communication with users through voice-based or text-based interfaces. These chatbots utilize machine learning techniques and Natural Language Processing (NLP) algorithms to analyze and comprehend user queries, and responses, and perform specified tasks. Chatbots find applications in diverse fields, including healthcare, business, finance, education, entertainment, and more.
The project utilizes the following technologies and tools:
- Python
- Flask
- PyCharm
- Natural Language Processing (NLP)
- -Tinker
This project aims to develop a Chatbot Song Recommendation System, a conversational agent engineered to enhance user experience and engagement by delivering custom-made song recommendations. The proposed model represents an advanced iteration of traditional recommendation systems by introducing a conversational and interactive element. Users can interact with the chatbot through text commands, thereby making the recommendation system more interactive and user-friendly. Notably, the model achieved a final loss of 0.0001 during training, signifying successful training and convergence. This indicates that the model has effectively acquired knowledge from the training data and can provide accurate music recommendations.
The proposed Chatbot Song Recommendation System holds great potential for various applications, including:
- Integration with song streaming platforms.
- Implementation in mobile applications.
By harnessing machine learning techniques and conversational capabilities, the Chatbot Song Recommendation system aspires to revolutionize the music recommendation experience in a more advanced and user-centric manner.
- Clone the repository to your local machine.
- Install the necessary dependencies using
pip install -r requirements.txt. - Run the Flask application using app.py