Music Algorithm is an innovative, research-driven platform that empowers users to generate music using five advanced algorithmic approaches: Markov Chains, Maximum Entropy models, Genetic Algorithms, Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs). The application allows exploration of varied musical styles and complexity by integrating multiple composition techniques into a single interface. Built primarily with Python and libraries such as TensorFlow, NumPy, Scikit-learn, Hugging Face, and SciPy, the platform provides both educational and creative value. While it offers versatility and innovative outputs, the system does require a learning curve and may produce inconsistent results depending on algorithm parameters and training data.