Machine Learning

Supervised Learning

 

Machine learning can be branched out into the following categories:
  • Supervised Learning
  • Unsupervised Learning
Supervised Learning is where the data is labeled and the program learns to predict the output from the input data.

Supervised learning problems can be further grouped into regression and classification problems.


Regression:
In regression problems, we are trying to predict a continuous-valued output.

Classification:
In classification problems, we are trying to predict a discrete number of values.


Unsupervised Learning

Unsupervised Learning is a type of machine learning where the program learns the inherent structure of the data based on unlabeled examples.

Clustering is a common unsupervised machine learning approach that finds patterns and structures in unlabeled data by grouping them into clusters.

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