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machine learning

Classification in ML is the job of predicting the type or class of an item from a limited set of possibilities. The categorization output variable is usually a category variable.

Learning regression has a set of issues in the machine language, where the outcome variable can take continuous variables. Calculating the price of an airline, for example, is a common regression task

Clustering, in a nutshell, is the problem of grouping related items together. It aids in the automated identification of comparable items without the need for operator involvement.

The number of predictor factors used to estimate the independent variable or objective is referred to as dimensionality. The number of variables in real-world datasets is frequently excessive.

Deep learning is a branch of machine learning that focuses on neural networks. Let’s go through several major deep learning models based on neural network architecture:

We discussed concepts from a variety of machine learning models above. The obvious question now arises: ‘Which of these models is the best?

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