hotspot-analysis

An Interactive Approach to Understanding Unsupervised Learning Algorithms

A software quality analysis tool based on hotspot prioritization and commits

A modern MikroTik hotspot manager

Analysis of when and where New York City (NYC) vehicle collisions occur with a focus on collisions involving pedestrians and cyclists.

Simple statistical functions that are useful for exploratory spatial data analysis (ESDA) on-the-fly in JavaScript

Contains Weekly Activites for the (ISTE 740) Geographic Information Sciences and Technologies Course @ RIT

Hotspot analysis on Big Data of a major taxi company using Apache Spark and Scala

Point your coding agent at your repo: an air-gapped sweep that finds your kill zone — files at high complexity × high churn × security. By Black Box Research Labs.

We will visualize the results of hotspot analysis and use kernel density estimation, which is the most popular algorithm for building distributions using a collection of observations. By the end of the course, you should be able to leverage Python libraries to build multi-dimensional density estimation models and work with geo-spatial data.

Spatial Hotspot Analysis on Geo-Spatial Data using Apache Spark and Scala

A geospatial data analytics project analyzing 26 years of UK economic (GVA) and deprivation (IMD) data. Features an ETL pipeline, spatial statistics, and interactive visualizations.

Spatiotemporal analysis of the course of the COVID-19 pandemic in Germany

Using LiDAR to characterize urban forest structure and composition and locate hotspots based on derived individual tree attributes

A hotspot refers to an area with a higher-than-expected concentration of events relative to a random distribution. n examining point patterns, the density of points within a specific area is compared to a model of complete spatial randomness, which represents a scenario where point events occur entirely randomly.

An ML-powered urban crime prediction and hotspot analysis system. Uses Logistic Regression, SVM, Random Forest, and a Keras MLP neural network to predict arrest likelihood and identify high-risk city zones. Built with Python, Flask, scikit-learn, and TensorFlow.