๐ The goal is to find a function f-hat that can make predictions y hat from the data.

๐ We want to find the best fit line (F-hat) that minimizes the errors between predicted and actual labels.

๐ก Two options to find the best fit line are parametric and non-parametric methods.

๐ Parametric methods involve making assumptions about the shape or form of the data.

๐ Nonparametric methods do not make assumptions about the shape or form of the data.

๐ Estimating the function is simplified when assuming a linear form.

๐ Parametric methods simplify the estimation problem by using known parameters.

๐ Nonparametric methods do not assume a specific form for the data distribution.

๐ Parametric models may not accurately match the true form of the data.

Choosing a linear model for non-linear data results in poor predictions.

Using a parametric method involves expressing output based on a linear equation.

Estimating the beta values allows for predicting sales in the advertising dataset.

๐ Parametric methods use predetermined parameters to make predictions based on specific assumptions.

๐ Nonparametric methods do not make explicit assumptions about the shape or form of the data and seek to estimate it based on the data points.

๐ Nonparametric methods have the advantage of being able to accurately fit a wider range of possible functions.

๐ Parametric methods assume a certain shape for the data, which can result in inaccurate predictions if the actual data shape is different.

๐ Nonparametric methods do not make any assumptions about the shape of the data, resulting in better fitting models.

๐ However, nonparametric methods require a larger amount of data for accurate estimation.

๐ Parametric methods rely on predefined assumptions about the data, while nonparametric methods do not.

๐ Nonparametric methods may struggle to accurately estimate the response for observations not included in the training dataset.

๐ Having a large, clean dataset with minimal outliers and noise is crucial for accurately estimating the best line in nonparametric methods.

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