Subject
4 entries
Unsupervised Learning
Bookmarks
ART: Questions Are All You Need to Train a Dense Passage Retriever
ART (Autoencoding-based Retriever Training) trains dense retrievers without labeled question-passage pairs — only questions and an unpaired document collection. This removes the main bottleneck for deploying dense retrieval in new domains where annotation is expensive.
Models and Algorithms for Unlabelled Data
Vaibhav Verdhan's Manning book on unsupervised learning algorithms, covering clustering, dimensionality reduction, and anomaly detection with Python implementations on real-world datasets. Practical in orientation — stronger on applied case studies than mathematical rigor.
UFLDL Tutorial — Stanford
Andrew Ng's Stanford UFLDL Tutorial — the primary self-study resource for deep learning before MOOCs existed. Teaches sparse autoencoders, PCA, CNNs, and deep belief networks with mandatory from-scratch implementation exercises.
Introduction to One-Class Support Vector Machines
A practical introduction to one-class SVMs — the variant of Support Vector Machines used for anomaly detection and novelty detection when you only have examples of normal behavior. Useful when collecting labeled anomaly examples is impractical or impossible.