L2 Regularization in Diabetes Dataset Analysis

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Dimensionality Reduction: PCA and LDA

Covers dimensionality reduction techniques like PCA and LDA, clustering methods, density estimation, and data representation.

Supervised Learning in Financial Econometrics

Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.

PCA: Directions of Largest Variance

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Air Pollution Data Analysis

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Generalized Linear Regression

Explores generalized linear regression, logistic regression, and multiclass classification in machine learning.

Overfitting, Cross-validation & Regularization

Explores model complexity, overfitting, and the role of cross-validation and regularization in machine learning.

Data Visualization: Techniques, Tools & Concepts

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Machine Learning Basics

Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.