Introduction in Machine Learning | Machine Learning


Machine Learning: Machine Learning is a method of teaching machines/computers to make a prediction based on some data and experience. It is applied in an incredibly wide variety of application areas. In briefly, Machine learning is an application of artificial intelligence that automates analytical model building by using an algorithm that iteratively learns from data without being explicitly programmed. A system to ask questions and answers.


Supervised Learning: Supervised learning is concerned with teaching the model with knowledge and allow it to understand and then predict the future instances using that knowledge. It deals with labeled data. The model is trained using labeled data so it can predict the future outcome with respect to the sample data.


Unsupervised Learning: Unsupervised learning uses a machine learning algorithm that draws the conclusion on unlabeled data.

It has more difficult algorithm because we have very low information of data since we don't know what kind of data we are dealing with.



Reinforcement Learning: Reinforcement learning is an area of machine learning, where an agent learn how to behave in an environment by performing an action and seeing the results.