This repository provides a hyperparameter optimization implementation for machine learning algorithms, accompanying a paper on hyperparameter optimization theory and practice. It includes sample code for regression and classification problems using the Boston-Housing and MNIST datasets, covering algorithms such as random forest, SVM, KNN and artificial neural networks.
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A 2003 book by David J.C. MacKay published by Cambridge University Press, covering information theory, inference, and learning algorithms. The site offers corrections, software, and downloadable figures. It lists a price of £35.00 or $60.00.
github.com
Desbordante is a high-performance open-source data profiler. It uses a variety of algorithms to discover different patterns in data and supports running data cleaning scenarios using these algorithms. The tool is available as a console version and an easy-to-use web application.
mvsep.com
MultiSong Leaderboard is a ranking page on the MVSEP music and voice separation platform. It evaluates multisong audio separation algorithms using metrics including SDR, SI-SDR, L1 frequency, log WMSE, aura STFT, aura MRSTFT, bleedless, and fullness, with rankings updated every three hours. The page lists top-performing algorithms and their scores for separation tasks such as bass, drums, other stems, vocals, and instrumentals.
stepbystepml.com
StepByStepML provides free online machine learning calculators that solve algorithms step-by-step for computer science exams. Users input a dataset and the site shows the full manual calculation for algorithms including K-Means, Minimax, KNN, A* Search, and evaluation metrics. Theory guides accompany the interactive solvers, and the site states it is built for CS students.
github.com
AIF360, or AI Fairness 360, is a comprehensive toolkit that provides fairness metrics for datasets and machine learning models. It includes explanations for these metrics and algorithms to mitigate bias in data and models. The project is developed by the Trusted-AI community on GitHub.
github.com
Devika is an open-source implementation of an Agentic Software Engineer, initially started as an alternative to Devin. It uses large language models, planning and reasoning algorithms, and web browsing to develop software from human instructions. The project is in an early experimental stage, and the repository notes that there are unimplemented or broken features.
home.work.caltech.edu
An introductory machine learning course taught by Caltech Professor Yaser Abu-Mostafa, recorded from a live broadcast and available as a free online MOOC. It covers basic theory, algorithms and applications across 18 lectures, with homework sets and a final exam. Prerequisites are basic probability, matrices and calculus.
github.com
Magenta is a research project exploring machine learning in art and music creation, developing deep learning and reinforcement learning algorithms for generating songs, images, and drawings. It also explores tools letting artists and musicians extend their processes with these models. The repository is archived and read-only.