A classified list of meta learning papers based on realm.

Learn the theory, math and code behind different machine learning algorithms and techniques.

[NeurIPS 2023] The official implementation of "Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition" .

ML course project: investigation on common perceptions of same neural network model with different random seed

📓 Chapter summaries adapted from the textbook "Understanding Machine Learning"

Implementation is to use gradient descent to find the optimal values of θ that minimize the cost function.

This repository hosts a progressive series of implementations (Code_v1, Code_v2, and beyond) for deterministic β*-optimization in the Information Bottleneck framework. Includes symbolic fusion, multi-path inference, and Alpay Algebra–driven critical point validation (β* = 4.14144).

A growing list of papers, books, courses and blogs related to machine learning theory and optimization

Emergent Computational Epistemology: studying AI’s emergent behaviors as non-human epistemic systems.

Towards understanding Machine Learning theory in 69 days :)

My personal projects of re-learning machine learning and deep learning algorithms

Reproducing the results in "Implicit Regularization in ReLU Networks with the Square Loss" using Matlab

The homework assignments of 'Machine Learning' from Stanford University in Coursera

Implementation of a simple Decision Tree Classifier, entirely made in Swift

AI labs - solutions