Machine learning techniques have found a wide range of applications in weather, climate, ocean, hydrology, and disease predictions. In recent times, these techniques are being increasingly used to predict extreme events such as malaria outbreaks, heat waves, cold spells, flooding, droughts, tropical cyclones, typhoons, El Nino/Indian Ocean Dipole events among many others. In addition, machine-learning techniques are helping researchers to improve parameterization schemes in numerical prediction models. Machine-learning is also being used to improve numerical model predictions by providing methods to reduce biases and improve the horizontal resolution of the predictions. The aim of this session is to bring together researchers working on various techniques of machine learning to enhance the understanding and skill of weather, climate, ocean, hydrology and disease predictions for the benefit of the society.