Supervised machine learning

In this blog post, we will talk about what supervised machine learning is and its real-life world application. Supervised machine learning algorithms make use of labelled datasets to make predictions. Labelled datasets are already classified so a supervised ML algorithm is learning to make predictions from historical data in this case. Supervised ML algorithms are classified into two kinds of algorithms:

Regression and Classification

Regression is a kind of ML algorithm used to predict a continuous value from a given data point. It can be used to predict house prices given a set of features. Classification is another kind of supervised ML algorithm is used to assign a label or category to a set of data points. An example of applying classification to a real world scenario is classifying images.

Some of the most popular supervised machine learning algorithms include:

• Linear regression: This is a simple but powerful algorithm that can be used for both classification and regression tasks.

• Logistic regression: This is a type of regression algorithm that is specifically designed for classification tasks.

• Support vector machines (SVMs): SVMs are a powerful algorithm that can be used for both classification and regression tasks.

• Decision trees: Decision trees are a simple but effective algorithm that can be used for both classification and regression tasks.

• Neural networks: Neural networks are a powerful algorithm that can be used for a variety of tasks, including classification, regression, and natural language processing.

Check out the video on machine learning, on my youtube channel:

https://www.youtube.com/channel/UCnC0m1H0AHgtXy_oUp4zTPw