Abhishek Majumdar Amardeep Sharma Data mining is the process of analysing vast amounts of data from various sources to extract useful information. This is done through the discovery of previously unknown patterns, correlations, and anomalies, which can then be used to predict future outcomes. On other hand, machine learning, takes things further by using algorithms and an iterative process to learn from new data and automatically become better at analysis and prediction. It can do this without the need for human intervention.

Abhishek Majumdar Amardeep Sharma Data mining is the process of analysing vast amounts of data from various sources to extract useful information. This is done through the discovery of previously unknown patterns, correlations, and anomalies, which can then be used to predict future outcomes. On other hand, machine learning, takes things further by using algorithms and an iterative process to learn from new data and automatically become better at analysis and prediction. It can do this without the need for human intervention.

Abhishek Majumdar Amardeep Sharma All the classifier comes under Machine Learning.

Data mining is the art of sorting through large databases and finding patterns in the data. The various stages of data ming are getting the data from data sources, data analysis, modelling and finally deploying the model in production/coming up with insights or recommendations. It is in the modelling phase where various statistical and machine learning methods are used such as regression, clustering, association rule mining, classification, etc. depending on the context.

So to answer your question, a classifier does come under Machine learning.

Machine learning can extract the information automatically, It uses data mining techniques and other learning methods to predict future outcomes.

Data mining is defined as the computational process of analyzing large amounts of data in order to extract patterns and useful information. It uses the techniques of machine learning in order to extract these important and useful data.

This question is another version of an older one here: https://www.researchgate.net/post/What_is_the_difference_between_machine_learning_and_data_mining

Data mining relates with the general analyzing of large data sets and generating the most feasible solution through a model algorithm ti suit your business or project.

Machine Learning in the other hand is deep understanding of the behavior of the model(algorithm) from the scratch i.e. the understanding of the mathematical notations and the working process.

Understanding machine learning will help you in a much much better way of understanding data mining but the vice versa is not possible.

Data mining only lets you play with the data set but you may be in a dilemma of which model suits best for your project.

This will not be the case with Machine Learning.

Data mining is mining of information from existing data. Machine learning contains the principles of data mining or machine learning can use in data mining.

Data mining is an information source for machine learning. In machine learning we first teach machines to perform naturally. There are different computational algorithms to learn from data. Thus Machine learning look at patterns and learn from them and easily adapt its behavior for future occurances.or we can say, in machine learning computers have the ability to learn without being explicitly programmed.