Читать книгу Enterprise AI For Dummies - Zachary Jarvinen - Страница 35

Machine learning (ML), a subset of artificial intelligence, enables users to learn from historical data to achieve a desired outcome. It powers targeted ads, personalized content, song recommendations, predictive maintenance activities, and virtual assistants.

ML mimics human learning by absorbing information. Humans learn by reading, watching, listening, and doing. ML learns by processing historical data. For example, a human’s knowledge of elephants is based on historical experience, such as going to the zoo, riding an elephant, watching a documentary, and reading a book. ML gains knowledge of elephants by processing text and images.

The learning phase consists of these steps:

1 Sample historical data (machine activity, customer attributes, and transactions).

2 Apply algorithm to historical data to learn key patterns and trends.

3 Generate a model or set of rules or instructions.

The prediction phase consists of these steps:

1 Load the existing model.

2 Apply the model to new data.

3 Predict the likelihood of an outcome (in other words, customer churn).

The output of the prediction phase feeds back into the input of the learning phase to refine the model.