Frequentists like to give you a perfect answer the first time by computing everything at once. Seeing the world like pure math. For example giving an unbiased dice of 6 faces, the likelihood to have a 6 the first time is = 1/6.
Bayesians like to walk in the park, and see step by step how things go. The more they walk, the more accurate the result will be. For example at step 5 with 1st roll: 1, 2sd: 6, 3rd: 3, 4th: 1, 5th: 2, you will have (1 + 0 + 0 + 1 + 0) / 5 = 0.4. At step 6 with a roll 5 you will have (1 + 0 + 0 + 1 + 0 + 0) / 6 = 0.333. The answer being closer and closer to the true answer after each roll, each step. Ultimately with enough rolls, bayesians will start to give you an answer close to the frequentists' one.
Bayesians like to walk in the park, and see step by step how things go. The more they walk, the more accurate the result will be. For example at step 5 with 1st roll: 1, 2sd: 6, 3rd: 3, 4th: 1, 5th: 2, you will have (1 + 0 + 0 + 1 + 0) / 5 = 0.4. At step 6 with a roll 5 you will have (1 + 0 + 0 + 1 + 0 + 0) / 6 = 0.333. The answer being closer and closer to the true answer after each roll, each step. Ultimately with enough rolls, bayesians will start to give you an answer close to the frequentists' one.