We are trying to plot an advance heatmap plot here which can be broken into hourly and monthly basis for multiple years for 24 hours in a given day

A heatmap visualization library for sighting intensity of data at geographical points contained in generic CSV files

Data surrounding an Instagram page’s engagement during the month of July was imported and manipulated to plot a colour-encoded matrix that revealed general patterns in their dataset. The final heatmap displays data from Instagram that identifies the best time of the day and day of the week to run social media marketing campaigns.

A short exploration of semi-supervised learning for image classification from the Kaggle retinal disease detection dataset. Also - gradCAM heatmaps for visualizing model activation.

Image classification on lung and colon cancer histopathological images through Capsule Networks or CapsNets.

Generate a noise pollution heatmap which can be visualised in google maps using jupyter notebook.

This is a Google tag manager template for Microsoft Clarity tag

University campus heatmap based on open data datasets. Students school project.

Disease Spread and Social Response Spread Simulation

Calendar heatmap svg generator written in go

Gaussian Navie Bayes Classifier was applied on IRIS dataset. Different types of normality tests were used to introduce the normality concepts.

Ideal Interface for Data Acquisition Systems and Control Robotics. Combining Core Java, OpenCV, GCP, various APIs in the journey towards ultimate sophisticated controller interface.

High memory usage reference implementation.

A Python program which uses strava .gpx files to create a heatmap to show the distribution of work out locations.

recursive method for heatmap calculation from given points.

Created a heatmap to showcase the avg. tips left by groups during lunch & dinner

fast calculation of heatmap from given points.

This is a study case to cluster and group customers based on their data and consumption behaviour data, analyze the core characteristics of user groups.

This is a case study of RED company based on user data and consumption behavior data. It uses Python to build a linear regression model to predict the changes in the user's purchasing amount and find the factors that have a greater impact on users' purchasing amount. The linear regression effect of the data provided is not good and it is only us…

Determining ideal vacation spots by analyzing weather data around the world.