A classified list of meta learning papers based on realm.
-
Updated
Sep 29, 2022
A classified list of meta learning papers based on realm.
Learn the theory, math and code behind different machine learning algorithms and techniques.
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"
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).
My personal projects of re-learning machine learning and deep learning algorithms
Implementation is to use gradient descent to find the optimal values of θ that minimize the cost function.
A growing list of papers, books, courses and blogs related to machine learning theory and optimization
Towards understanding Machine Learning theory in 69 days :)
Reproducing the results in "Implicit Regularization in ReLU Networks with the Square Loss" using Matlab
AI labs - solutions
The homework assignments of 'Machine Learning' from Stanford University in Coursera
Implementation of a simple Decision Tree Classifier, entirely made in Swift
Machine Learning Algorithms from scratch
Add a description, image, and links to the machine-learning-theory topic page so that developers can more easily learn about it.
To associate your repository with the machine-learning-theory topic, visit your repo's landing page and select "manage topics."