Slide 1: RL-based Music Recommendation: Leveraging SAC and PPO. Slide 2: The Evolving Soundscape of Music Recommendation. Slide 3: Reinforcement Learning Fundamentals for Music. Slide 4: Overcoming Recommendation Hurdles with RL. Slide 5: Soft Actor-Critic (SAC): The Entropy-Maximalist. Slide 6: Proximal Policy Optimization (PPO): The Stable Learner. Slide 7: Integrating SAC & PPO: A Hybrid Approach?. Slide 8: System Architecture for RL Music Recommendation. Slide 9: Training, Evaluation & Performance Metrics. Slide 10: Results and Discussion: The Promise of RL in Music. Slide 11: Conclusion & The Future of Musical AI. Slide 12: Thank You!