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Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
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github.com
General Machine Learning library using Numenta’s Cortical Learning Algorithm.
Helps teams build, deploy, observe or operate machine-learning systems.
github.com
Objective-C version of Google Palette algorithm in Java.A tool to extract the main color of an image.
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JavaScript implementation of the k nearest neighbors algorithm for supervised learning.
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Just a simple implementation of K-Nearest Neighbors algorithm using with a bunch of similarity measures.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
home.work.caltech.edu
Introduction to machine learning covering basic theory, algorithms and applications.
libra.cs.uoregon.edu
Algorithms for learning and inference with discrete probabilistic models.
making.lyst.com
A Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback.
machinelearningmastery.com
About helping professional programmers confidently apply machine learning algorithms to address complex problems.
mahout.apache.org
Distributed linear algebra framework and mathematically expressive Scala DSL.
Open-source project that supports software development with code generation, analysis, debugging, or documentation.
github.com
Metric Learning Algorithms in Python.
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A set of functions to support the development of machine learning algorithms.
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Framework that implements AutoML algorithms for model architecture search at scale.
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Algorithm capable of fully capturing the impact of data drift on performance.
nsynthsuper.withgoogle.com
An experimental physical interface for the NSynth machine learning algorithm.
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Parris, the automated infrastructure setup tool for machine learning algorithms.
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This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.
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Python Machine Learning Pentesting Toolbox for Adversarial Attacks. Works with LLMs, DNNs, and other machine learning algorithms.
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Algorithmic Trading with Machine Learning.
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Basic sampling algorithms for Julia.
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A collection of algorithms for image processing in Python.