Multimodal Data Analysis is the process of integrating and analyzing data from multiple sources or types, such as time series data, text, and images, to generate comprehensive and explainable insights. In the project, this approach is combined with explainable AI techniques to ensure that the data-driven forecasts are not only accurate but also easily interpretable and actionable across various modalities.

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Introducing Our New Project: Time Series Language Model for Explainable AI

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Our new project, Time Series Language Model for Explainable AI, represents a significant leap forward in the field of forecasting and explainable AI. By combining advanced forecasting techniques with explainable AI, we are paving the way for a future where data-driven insights are not only accurate but also comprehensible and actionable.

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