Artificial Intelligence By Example

Machine learning versus traditional applications

Reinforcement learning based on stochastic (random) processes will evolve beyond traditional approaches. In the past, we would sit down and listen to future users to understand their way of thinking.

We would then go back to our keyboard and try to imitate the human way of thinking. Those days are over. We need proper datasets and ML/DL equations to move forward. Applied mathematics has taken reinforcement learning to the next level. Traditional software will soon be in the museum of computer science. 

An artificial adaptive thinker sees the world through applied mathematics translated into machine representations.

Use the Python source code example provided in this chapter in different ways. ...