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Recent developments in machine learning have greatly benefited quantitative finance, allowing for more accurate forecasting and enhanced risk management strategies. Techniques such as recurrent neural networks, reinforcement learning, and generative adversarial networks have shown potential in areas such as time series forecasting, algorithmic trading, and synthetic data generation. Additionally, explainable AI methods have been developed to provide model interpretation and support decision-making processes.