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Locality Sensitive Hashing, fuzzy-hash, min-hash, simhash, aHash, pHash, dHash。基于 Hash值的图片相似度、文本相似度
distill large scale web page text
Search your object with hash
Recommendation System on cryptocurrency, using data collected from users' tweets + 10-Fold Cross Validation ( Based on the cryptocoins from each user's tweets, the program runs algorithms on the data, resulting in the recommendation of other cryptocoins for each user) ( readme in greek but soon to be translated in English )
An implementation of Locality sensitive hashing
Dataset deduplication using the spark ML lib and Scala
Image Retrieval implementation using Deep Learning and Kernelized Locality-Sensitive Hashing
:chart_with_upwards_trend: kNN using LSH and Hypercube projection & Clustering using kMeans++ for n-dim polygonal curves and time series
Image classification and unsupervised learning using latent space vectors produced by convolutional neural nets together with the original vectors space
This is a task using python to find number of similar songs within the provided songs set.
A Robust Library in C# for Similarity Estimation
Vectors - Nearest neighbor search and Clustering using LSH, Hypercube (and Lloyd's only at the clustering) algorithms with L2 metric.
In this repository you can find an implementation of LSH (Local | Sensitive Hashing) and Finesse algorithms, designed to find similar data based on their hashes
Implementation tasks for multiple algorithms to process massive data. The algorithms are written in Python.
📈|Time Series - Nearest neighbor search and Clustering using LSH, Hypercube (and Lloyd's only at the clustering) algorithms with metrics: L2, Discrete and Continuous Fréchet.