Locality-Sensitive Hashing Courses and Certifications

UofU Data Science

Locality-Sensitive Hashing and Distribution Distances - Lecture 7

Discover LSH techniques for fast similarity search using hash functions and banding, plus explore distribution distances like KL, Hellinger, and Wasserstein metrics.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

UofU Data Science

Data Mining: Locality-Sensitive Hashing for Similarity Measures - Lecture 6

Dive into Locality-Sensitive Hashing (LSH) techniques, exploring min-hash algorithms, Jaccard similarity, and triangle-based approaches for efficient data mining and similarity search.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video

Mining Massive Datasets

24 reviews

The course is based on the text Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who by coincidence are also the instructors for the course.

• edX
• 7 weeks, 5-10 hours a week
• On-Demand
• Free Online Course (Audit)

• Best of All Time

James Briggs

How LSH Random Projection Works in Search - Python

Explore efficient similarity search using Locality Sensitive Hashing (LSH) and Random Projection. Learn how to handle large-scale data and implement approximate search techniques in Python.

• YouTube
• 19 minutes
• On-Demand
• Free Video

Simons Institute

A Quasi-Monte Carlo Algorithm for Smooth Kernel Evaluation

Explore a novel data structure for density queries, combining discrepancy theory and LSH to build sparse coresets and enhance smooth kernel evaluation algorithms.

• YouTube
• 42 minutes
• On-Demand
• Free Video

UofU Data Science

Nearest Neighbor Search - Algorithms and Data Structures - L5

Explore nearest neighbor search algorithms from 1D binary trees to high-dimensional LSH and hierarchical navigable small world graphs for efficient data retrieval.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video

James Briggs

Locality Sensitive Hashing for Search with Shingling + MinHashing - Python

Learn efficient similarity search using Locality Sensitive Hashing (LSH) with shingling and MinHashing techniques in Python. Explore implementation steps, from data preprocessing to LSH tuning, for approximate nearest neighbor search.

• YouTube
• 27 minutes
• On-Demand
• Free Video

EuroPython Conference

Speeding Up Search With Locality Sensitive Hashing

Explore locality sensitive hashing for faster search and similarity comparisons, with practical Python implementations and real-world applications in image search and collaborative filtering.

• YouTube
• 24 minutes
• On-Demand
• Conference Talk

Optimized Data Preparation for Large-Scale LLMs

Master efficient data preparation strategies for training large-scale LLMs through scalable collection, deduplication, filtering, and augmentation techniques to optimize datasets.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Stuff Made Here

World's Hardest Jigsaw vs. Puzzle Machine - All White

Watch a puzzle machine tackle the world's hardest jigsaw—an all-white puzzle. Explore image processing, mathematical algorithms, and innovative engineering solutions in this challenging project.

• YouTube
• 22 minutes
• On-Demand
• Free Video

James Briggs

Vector Similarity Search and Faiss Course

Master vector similarity search techniques and Faiss implementation through hands-on practice with traditional methods, advanced indexing, and performance optimization strategies.

• YouTube
• 6 hours 16 minutes
• On-Demand
• Free Video

Yannic Kilcher

Reformer - The Efficient Transformer

Discover how Reformer revolutionizes Transformer models, reducing memory usage and enabling processing of longer sequences through innovative techniques like Locality Sensitive Hashing and Reversible Networks.

• YouTube
• 29 minutes
• On-Demand
• Free Video

Discover AI

Reversible Transformer - GPU Memory Optimization Using ReFORMER and Reversible Residual Layers

Delve into GPU memory optimization techniques for transformers, exploring reversible residual layers and locality-sensitive hashing to enhance deep neural network efficiency and performance.

• YouTube
• 18 minutes
• On-Demand
• Free Video

LASCON

Malware Clustering - Static and Dynamic Behavior Analysis

Explore innovative malware clustering techniques using static and dynamic behavior analysis, machine learning, and similarity search for robust, scalable, and repeatable results.

• YouTube
• 49 minutes
• On-Demand
• Free Video

0xdade

Time Signature Based Matching for Data Fusion and Coordination Detection in Cyber Relevant Logs

Methodology for detecting automated behavior in cyber logs using temporal pattern matching, scalable through locality sensitive hashing. Applications include anomaly detection and data fusion.

• YouTube
• 23 minutes
• On-Demand
• Conference Talk