Difference between decision trees among the forest

in Machine Learning with Decision Trees and Random Forests / Random Forest as Ensemble Learning

When building the different decision trees for my set of data, what are the differences between each tree ? Features used; using different features in different trees or maybe something else ?

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Difference between decision trees among the forest

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