Akella Dattatreyulu Could you specify which task you want to work on exactly? Traditionally, to encode time dependant tasks you would use a recurrent neural network (RNN)

https://towardsdatascience.com/a-brief-introduction-to-recurrent-neural-networks-638f64a61ff4#:~:text=Python%20using%20tensorflow%20.-,Recurrent%20Neural%20Network%20(RNN),in%20a%20short%20term%20memory.

determining causality direction between two events is a challenging task that requires careful consideration, domain knowledge, and appropriate statistical and machine learning techniques. While artificial intelligence and machine learning can assist in causal inference, they are not a substitute for sound experimental design and understanding of the underlying context. A combination of correlation analysis, causal inference techniques, experimental design, and expert validation is often necessary to establish meaningful causality. Additionally, creating a causal map or directed graph can visually represent the causal relationships between the events. However, it is crucial to exercise caution when making causal claims and be aware of the limitations and assumptions of the methods used. Causality is a powerful concept that requires rigorous analysis and continuous refinement.