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Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.
Linear regression is used to predict the value of a dependent variable based on the value of one or more independent variables.
It assumes a linear relationship between the independent and dependent variables.
The goal of linear regression is to find the best-fitting line that minimi...
Random Forest is an ensemble learning method used for classification and regression tasks.
Random Forest is made up of multiple decision trees that work together to make predictions.
Each tree in the Random Forest is trained on a random subset of the training data.
The final prediction is made by averaging the predictions of all the individual trees.
Random Forest is known for its high accuracy and ability to handle large ...
They will give you some dataset from renewable domain and will ask you to forecast.
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Understanding outliers, missing values, overfitting, and underfitting in data science.
Outliers are data points that significantly differ from other data points in a dataset.
Missing values are data points that are not present in a dataset.
Overfitting occurs when a model learns noise in the training data rather than the underlying pattern.
Underfitting occurs when a model is too simple to capture the underlying pattern in...
Understanding outliers, missing values, overfitting, and underfitting in data science.
Outliers are data points that significantly differ from other data points in a dataset.
Missing values are data points that are not present in a dataset.
Overfitting occurs when a model learns noise in the training data rather than the underlying pattern.
Underfitting occurs when a model is too simple to capture the underlying pattern in...
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