Often confused with Artificial intelligence, machine learning actually takes the process one step further by offering the data necessary for a machine to learn and adapt when exposed to new data. I would define it as the self-learning capability of the machines by modern computing principles. Fundamentally, it is designed and built by reading mined data, creating a new algorithm through AI, and then updating the current algorithms in a highly dynamic fashion according to the newly learnt task. In turn, the self learning matures with time and with more experience/executions.

ML has the following few fundamental capabilities:

• Generalizing information from large data sets
• Detecting and extrapolating the data patterns
• Applying derived information to the needy solutions
• Executing the appropriate actions

By design, the preceding execution steps are based on self-intelligent algorithms. Obviously, certain parameters must be set up at the beginning of the machine learning process so that the machine is able to find, assess, and act upon new data.