Simple calculation to render cheap water effects.

Julia package for kernel functions for machine learning

simple but efficient kernel regression and anomaly detection algorithms

A suite of classification clustering algorithm implementations for Java. A number of partitional, hierarchical and density-based algorithms including DBSCAN, k-Means, k-Medoids, MeanShift, Affinity Propagation, HDBSCAN and more.

Machine learning kernels in Julia.

🔍 Code to read / write the Process Memory from the Kernel 🔧

Operating System OS/161 Kernel Development

Random Fourier Features

Foundational library for Kernel methods in pattern analysis and machine learning

ksocket: easy TCP/UDP networking in kernel space

**Supervised-Learning** (with some Kaggle winning solutions and their reason of Model Selection for the given dataset).

💡This repository contains all of the lecture exercises of Machine Learning course by Andrew Ng, Stanford University @ Coursera. All are implemented by myself and in MATLAB/Octave.

LIME for TimeSeries enhances AI transparency by providing LIME-based interpretability tools for time series models. It offers insights into model predictions, fostering trust and understanding in complex AI systems.

A Julia package work with spectral densities of stationary kernels.

Multiple Kernel Least Squares Suport Vector Machine provide classification model.

The implementation of systems calls, lock, Virtual Memory and other file system implementation on OS161

📈 Desktop app for testing and ploting fuzzy operators