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30. Regularization Demo: Polynomial Regression with Noise Reduction

30. Regularization Demo: Polynomial Regression with Noise Reduction

In this demo notebook, we'll explore how regularization helps us identify the true underlying function in noisy data. We'll examine a practical example where we have a known underlying function with added random noise, and demonstrate how to use regularization techniques along with polynomial features to recover the true signal. The discussion will cover how to properly set up our environment with necessary libraries (OS, pandas, NumPy, Matplotlib, and Seaborn) and access our data files. This hands-on demonstration will help you understand how regularization can help distinguish between meaningful patterns and random noise in your data.

Видео 30. Regularization Demo: Polynomial Regression with Noise Reduction канала My Course
ML demonstration ML implementation Python libraries Python programming data analysis data preprocessing data visualization model fitting model optimization noise reduction polynomial regression regularization demo statistical learning underlying function
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20 мая 2025 г. 22:00:35
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