Running MLflow experiments

Portfolio of data science projects completed by me for academic, self-learning, and hobby purposes.

Demystifying ~400K layoffs to analyze underlying causes and predict future trends

A data mining study was conducted to determine the correlations between factors associated with high and low suicide rates in countries worldwide. Pandas and mlxtend were used in Python, as well as the data mining program Rapidminer.

Generated movie recommendations using association rule mining.

Online Coding Internship By Suven Consultants & Technology. During this Internship, I have worked on projects related to Data Analytics, Machine Learning, NLP and Association Rule - Mining.

"SmartCart" is a cutting-edge e-commerce tool 🌟 that leverages predictive analytics to provide personalized shopping recommendations and optimize inventory management, tailored for businesses aiming to enhance customer engagement and sales 🚀.

Predict the effect of genetic mutations in cancer tumors and classify them based on text clinical literature.

Mlxtend, Association_rules, Apriori, FP Growth

Messing around with Databases Dimensionality Reduction and classification using Multi Layers Perceptron. (simple academic research)

Machine learning models for enhanced fraud detection in e-commerce transactions, exploring feature engineering, distance prediction, and clustering analysis.

Learn more about market basket analysis with a hands-on project

In This Notebook I've built an Association rules Recommendation system, that make relations between itemsets and recommend the items that related to what user purchased.

Implementation of Apriori, FP-Growth, and ECLAT algorithms on natural language data

OpenClassrooms Data Analyst 2022-2023 - Projet 6

Предоставлен файл с сервера. Вам нужно спарсить его содержимое, создать базу данных под данные, вставить данные в базу данных, удаленно подключиться к базе данных и проанализировать данные.

The repo focuses on my works in data science

Subreddit recomendation system based on association rules harvested using data mining algorithms.

This code performs association analysis on a sales dataset, using the Apriori algorithm. The dataset is loaded from an Excel file, and a basket of items is created for each transaction. The Apriori algorithm is then applied to find frequent itemsets and association rules based on the support, confidence, and lift metrics.