An Open Source PHP Reporting Framework that helps you to write perfect data reports or to construct awesome dashboards in PHP. Working great with all PHP versions from 5.6 to latest 8.0. Fully compatible with all kinds of MVC frameworks like Laravel, CodeIgniter, Symfony.

Summarize Massive Datasets using Submodular Optimization

The pmartR R package provides functionality for quality control, normalization, exploratory data analysis, and statistical analysis of mass spectrometry (MS) omics data, in particular proteomic (either at the peptide or the protein level), lipidomic, and metabolomic data.

A web application to summarize a given input data

A Python library for day to day data analysis and machine learning. This aims to make data building, cleaning and machine learning much much faster. A library of extension and helper modules for Python's data analysis and machine learning libraries.

Soccer Game Analysis project

FD-RMS

R package for the exploration and visualization of proteomics data obtained with the process of fractionation

rankextractplus extracts and structures ranked info from text, organizing data for easier comparison and analysis.

A new package is designed to analyze financial news headlines and extract key structured information such as company names, financial targets, timeframes, and goal updates from text inputs. It simplif

This repository contains my take on making a warehouse summary. Any advice or comments are greatly appreciated!

Code to find rows of high leverage in a data stream.

A comprehensive web scraping and content summarization library with AI-powered features

A new package is designed to analyze and summarize business strategy narratives, investor communications, or crowdfunding campaign descriptions to extract structured insights about startup funding act

copyright-stats-extractor parses headlines/articles on digital copyright enforcement to auto‑extract stats like takedown counts, year, and parties.

Code and tutorial to create data summaries in R.

SAS for Data Science.

Predicition of Cardiovacular Disease in an Individual using Machine Learning Algorithms