Machine Learning refers to machine learning to use big data sets instead of hardcoded rules.

Machine Learning allows computers to learn on their own. This type of learning takes advantage of the computing power of modern computers that can easily handle large data sets.

Supervised and Unsupervised Learning

Supervised Learning involves using tagged data sets with inputs and expected outputs.

As you train an AI using supervised learning, you give it an input and say the expected output. If the output produced by AI is wrong, it adjusts its calculations. This process is repeatedly done over the dataset until it minimizes the error rate of Artificial Intelligence. An example of supervised learning is the weather-determining Artificial Intelligence. Learns to forecast the weather using historical data. These training data include inputs (pressure, humidity, wind speed) and outputs (temperature).

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