Simple calculation to render cheap water effects.
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Updated
Apr 25, 2017 - Swift
Simple calculation to render cheap water effects.
Julia package for kernel functions for machine learning
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
simple but efficient kernel regression and anomaly detection algorithms
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.
Multiple Kernel Least Squares Suport Vector Machine provide classification model.
📈 Desktop app for testing and ploting fuzzy operators
The implementation of systems calls, lock, Virtual Memory and other file system implementation on OS161
A Julia package for kernel functions on graphs
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