PyHelpers: An open-source toolkit for facilitating Python users' data manipulation tasks

Prepping tables for machine learning

This repository contains models that predict the obesity level of patients based on their eating/lifestyle habits and physical condition.

Privacy Engineering for the Generative AI era

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

Microsoft Stock Price (closing) Prediction using Stacked LSTM and ARIMA (6,1,6) models

This repository provides Python code for converting satellite data into a format suitable for deep learning models. It supports various deep learning architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory networks (LSTMs).

Easy to use Python library of customized functions for cleaning and analyzing data.

Atlantic - Automated Data Preprocessing Framework for Supervised Machine Learning

The LARGE LANGUAGE MODEL FOR HYDROGEN STORAGE project uses advanced natural language processing to improve research efficiency. It offers concise summaries and answers questions about hydrogen storage research papers, helping users quickly understand key insights and latest advancements.

Predicts housing prices using machine learning models on data from kaggle. Explores features like square footage and location through EDA. (Welcome to explore and experiment!)

A convenience tool for small-scale data pipelines in Python

This repository contains code for predicting house sales prices using machine learning models. It includes data preprocessing, model training, evaluation, and prediction on test data.

This project collects sensor data (accelerometer and gyroscope) from various activities using an Arduino Nano 33 IoT and classifies them with machine learning.

Machine learning project to forecast gig success and extent. It gathers data with Selenium Stealth, cleans and visualizes with pandas, numpy, and matplotlib, and predicts using sklearn's decision trees and random forest

Federated data Preprocessing via aggregated Statistics

🚀 Welcome to the AIML Repository! 📚✨ Dive into a treasure trove of AI and Machine Learning knowledge. 🤖💡 Explore meticulously curated notes, textbooks, and program resources. 📖👩‍💻 Your go-to source for mastering AIML in an exciting learning space! 🌐

A very basic implementation of a preprocessor for tabular data.

In this repo, my skills as a data scientist, exploring various data analysis, data preprocessing, and data visualization

Explore a variety of R-based data visualizations and models in this repository. Curated and crafted by a data enthusiast, these resources showcase the versatility of R in analytics and modeling.