Messing around with Databases Dimensionality Reduction and classification using Multi Layers Perceptron. (simple academic research)
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.
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.
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
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 🚀.
Mlxtend, Association_rules, Apriori, FP Growth
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
Association-Rules-Data-Mining-Books. Apriori Algorithm, Association rules with 10% Support and 70% confidence, Association rules with 20% Support and 60% confidence, Association rules with 5% Support and 80% confidence, visualization of obtained rule.
Apriori Algorithm Association rules with 10% Support and 70% confidence Association rules with 5% Support and 90% confidence Lift Ratio > 1 is a good influential rule in selecting the associated transactions visualization of obtained rule
Market basket optimisation/Used libraries: NumPy , Pandas, Matplotlib, Seaborn, Networkx, Warnings, Pycaret
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The repo focuses on my works in data science
Predict the effect of genetic mutations in cancer tumors and classify them based on text clinical literature.
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