In conventional programming, you determine the rules that will provide you with the expected result, whereas machine learning inverts this order, feeding the algorithm with existing results in order to constitute their own logic. That enables complex calculations that would require numerous rules otherwise. Conventional algorithms do not draw conclusions – they're entirely dependent on the coded logic determined by the programmer. Machine learning models, on the other hand, can learn. Their ability to process big data allows them to identify patterns and make predictions at an incomparably fast pace. Note that even though the machine learning algorithms have the ability to self learn, some may not involve automated reasoning. For instance, in expert systems, ML models are predefined to emulate the expert's behavior.