• Dr. Lokesh Jain
• Himanshu Kaushik

"Melody Insight" embarks on the journey of predicting song popularity through a meticulous and user-friendly process. The project initiates with robust data pre-processing, addressing missing values, outliers, and categorical encoding to ensure a clean and reliable dataset. This sets the stage for exploratory data analyses (EDAs) to glean valuable insights, enabling informed decision-making throughout the project. The heart of the project lies in the selection of the most accurate predictive model. Leveraging various machine learning algorithms, each model is assessed based on its performance scores, facilitating a nuanced comparison. This iterative model selection ensures the adoption of the most suitable algorithm for predicting song popularity with precision. To enhance user interaction, the project incorporates a graphical user interface (GUI) developed using Tkinter. This GUI serves as an intuitive platform, allowing users to effortlessly select their preferred artists, choose from the available songs, and explore comprehensive attributes of the selected song in a dedicated window. The user-friendly interface streamlines the selection process and promotes an engaging experience. Upon inputting desired attributes, users can initiate the prediction process by pressing a designated button. The system then provides both the predicted popularity score and the actual popularity score, empowering users with insights into the potential success of the chosen song. By seamlessly integrating data pre-processing, exploratory data analysis, model selection, and an interactive GUI, "Melody Insight" emerges as a versatile tool, catering to the needs of music enthusiasts, artists, and industry professionals seeking a deeper understanding of song popularity dynamics.

EDA, melody insight, iterative model, NLP

"Song Popularity Prediction Through Natural Language Processing ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 1, page no.e667-e671, January-2024, Available :http://www.jetir.org/papers/JETIR2401479.pdf

"Song Popularity Prediction Through Natural Language Processing ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 1, page no. ppe667-e671, January-2024, Available at : http://www.jetir.org/papers/JETIR2401479.pdf