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If you have just started machine learning then Scikit-learn is probably the essential library to start with. it is fairly easy to pick up and by learning how to use it, you will also gain a good grasp of the key steps in a typical machine learning workflow or pipeline.
Scikit-learn (formerly known as sklearn) is a free machine learning library for the Python programming language. Since it is very Simple and efficient tools for predictive data analysis. It provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction via a consistence interface in Python. It is also widely used in industry as well as in academic course .
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Introduction to Scikit-learn: This is an introductory video for the scikit-learn library in Python. In this you will learn the pre-requisites, the features and uses of the library along with a sample code in which we will import an inbuilt dataset from this library and view it.
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Linear Regression in Scikit-learn: This video takes a dive into the linear models of the scikit-learn library in Python. In this you will learn about Simple Linear Regression along with its code. You will also learn about certain metrics from the library to evaluate the model.
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Multiple Linear Regression in Scikit-learn: This video takes a dive into the linear models of the scikit-learn library in Python. In this you will learn about Multiple Linear Regression along with its code. You will also learn about certain metrics from the library to evaluate the model.
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