Machine learning or deep learning

With machine learning, algorithm options are selected and used to analyze data and data sources and, rather than make decisions on them, they learn from them so that they can use patterns or results found in the data to make decisions or predictions about a certain topic, or to solve a specific problem.

What this translates to is that instead of you programming or writing out each rule and instruction that needs to be used for a specific task such as making a prediction, the computer is trained using large amounts of data and algorithms which give it the ability to actually learn how to perform a task, make a prediction, solve a problem, or meet an objective in mind.

Note

Just how much data qualifies as enough data for successful machine learning?

Usually the bigger, the better, but in practice, you must gather a sufficient amount of data, based upon your intended purpose or need. Given a shortage of quantity, the wise data scientist should always focus...