Machine Learning is the science of getting computers to come to conclusions based on information but without being specifically programmed in how to accomplish said task.

Machine learning is a system designed to solve a problem. It works mathematically to produce the solution. The solution could be programmed specifically or worked out by humans manually, but without this need, the solutions come much faster.

A common machine learning model follows the following sequence:

• Giving a known data to the system is a set of data with a large array of possible variables connected to a known positive or negative result. This is used to train the system and give it a starting point. Basically, it now understands how to recognize and weigh factors based on the past data to produce a positive result.
• Once the system is conditioned with the starting data it is then fed new data but without the known positive or negative result. The system does not know the relationships of a new entity or whether an email is a spam or not. When it selects correctly it is given a reward though clearly not a chocolate bar. An example would be to give the system a reward value with a goal of hitting the highest number possible. Each time it selects the right answer this score is added to.
• Once the success metrics are high enough to surpass existing systems or meet another threshold the machine learning system can be integrated with the algorithm as a whole.

This model is referred to as supervised learning and it’s the model used in the majority of the Google algorithm implementations.

Another model of machine learning is the Unsupervised Model, this is the model used to group similar stories in Google News and one can infer that it’s used in other places like the identification and grouping of images containing the same or similar people in Google Images.

In this model, the system is not told what it’s looking for but rather simply instructed to group entities (an image, article, etc.) into groups by similar traits (the entities they contain, keywords, relationships, authors, etc.)

Paying more attention to the types of content that Google feels may fulfill a user’s intent (post, image, news, video, shopping, featured snippet, etc.) and work to provide it.

To know more about machine learning works in search engine industry:-  Prediction of trending technology- embellished