Unsupervised Learning
Showing 12 of 12 projects
Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility and transparency.
Python implementations of popular machine learning algorithms from scratch with interactive Jupyter demos and mathematical explanations.
Comprehensive cheatsheets and refreshers covering all key concepts from Stanford's CS 229 Machine Learning course.
A curated list of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
A curated collection of must-use resources for AI engineering, including books, courses, papers, frameworks, and tools.
A curated collection of papers, code, and resources for domain adaptation in machine learning.
A Python library providing extensions and utilities for data science and machine learning tasks.
A comprehensive Rust machine learning framework focused on preprocessing and classical algorithms, akin to scikit-learn.
A curated list of research papers, datasets, and resources for anomaly detection in time-series, video, and image data.
A Python library for outlier, adversarial, and drift detection in machine learning models, supporting tabular, text, image, and time series data.
An API-oriented Python framework for unsupervised learning on graphs, featuring node/graph embeddings and community detection.
An unsupervised learning framework for depth and ego-motion estimation from monocular videos using TensorFlow.
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