WHAT is Machine Learning

A typical machine learning tasks are to provide a recommendation. Recommender systems are a common application of machine learning, and they use historical data to provide personalized recommendations to users. In the case of Netflix, the system uses a combination of collaborative filtering and content-based filtering to recommend movies and TV shows to users based on their viewing history, ratings, and other factors such as genre preferences.

Reinforcement learning is another type of machine learning that can be used to improve recommendation-based systems. In reinforcement learning, an agent learns to make decisions based on feedback from its environment, and this feedback can be used to improve the recommendations provided to users. For example, the system could track how often a user watches a recommended movie and use this feedback to adjust the recommendations in the future.

Personalized recommendations based on machine learning have become increasingly popular in many industries, including e-commerce, social edia, and online advertising, as they can provide a better user experience and increase engagement with the platform or service.

The breakthrough comes with the idea that a machine can singularly learn from the data (i.e., an example) to produce accurate results. Machine learning is closely related to data mining and Data Science. The machine receives data as input and uses an algorithm to formulate answers