Tori: Character Forms and Monomials

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Textual Data Analysis: Classification & Dimensionality Reduction

Explores textual data classification, focusing on methods like Naive Bayes and dimensionality reduction techniques like Principal Component Analysis.

Algebraic Geometry: Forms and Maps

Covers the concept of forms in algebraic geometry and the implications of constructing Bloch(A) from glued copies of A.

Nearest Neighbor Classifier: Curse of Dimensionality

Explores the nearest neighbor classifier method, discussing its limitations in high-dimensional spaces and the importance of spatial correlation for effective predictions.

Computational Thinking Test: Evaluation and Design

Presents a test to evaluate computational thinking skills, discussing its design, analysis of previous tools, sample question, and study results.

Decomposition into Line Metrics: Example and Outlook

Covers the decomposition into line metrics, providing examples and discussing its implications.

Threshold Functions in Neural Networks

Explores threshold functions in neural networks for classifying data points based on positive and negative values.

Curse of Dimensionality in Deep Learning

Delves into the challenges of deep learning, exploring dimensionality, performance, and overfitting phenomena in neural networks.

Kernel Regression: Basics and Applications

Explores kernel regression, the curse of dimensionality, and random features in neural networks.

Linear Algebra Basics

Covers the basics of linear algebra, including linear maps, bases, and matrix operations.

Finite Difference Methods: Linear Systems and Band Matrices

Covers the application of finite difference methods to solve partial differential equations.