Association rule mining is a technique to identify underlying relations between different items.

Unsupervised ML algorithm for predictive modeling and time-series analysis

All codes, both created and optimized for best results from the SuperDataScience Course

Comparison of Apriori and FP-Growth Algorithm in accuracy metrics, execution time and memory usage for a prediction system of dengue.

Association rule mining using Apriori algorithm.

Implementation scripts of Machine Learning algorithms on Scikit-learn and Keras for complete novice..

This repository is created to represent the processing and the analysis that has been done on this online retail dataset.

This repository contains the three-part capstone project made for the DTU Data Science course 02450: Introduction to Machine Learning and Data Mining

Market Basket Analysis What is it? Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. For example, if you are in an English pub and you buy a pint of beer and don't buy a bar meal, you are more likely to buy crisps (US. chips) at the same time than somebody who didn't buy beer.

The purpose of this project is to recommend personalized products for segments by finding product associations.

Finding Association Rules between Location, Crime Type and Crime Outcome of Crime in England

Data science tutorials

Used association ruling to find out which products were frequently bought together. Aim is to drive higher sales volume and customer retention.

Data Science Practice Projects

Hear All Solution In R Language

Based on the Udemy Course "Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2024]"

In this repository, we will explore apriori and eclat algorithms of association rule learning models for market basket optimization.

Association rule generation using FP Growth algorithm

Book_Recommendation_Project

associative collaborative filtering recommender system

🚀 A hands-on AI/ML playground 🤖📊 — from NumPy, Pandas & Matplotlib basics to Supervised ML (Regression, Classification, SVM, Random Forest) and Unsupervised ML (Clustering, Dim. Reduction, Association Rules). Real-world projects 🛒📈 with rich visual outputs 🎨 — AI made practical.

Identifying best deals (recommended pairs for market optimization deals to optimize profits) using Apriori model which is an Association Rule Learning model.

Machine Learning Files

(ASSOCIATION RULE LEARNING) : We are given with 7501 transaction of a Famous Commodity Shop. We have to find the Best Suited Pair for Buy 1 Get 1 offer, that is to be given by the Shop Owner. So here I have used APRIORI Model to select most Relevant Pairs.

FPGrowth C++ implement

This repository is based on the lecture '고객데이터와 딥러닝을 활용한 추천시스템 구현'

Finding Associations Between Location, Crime Type and Crime Outcome in Swindon and Wiltshire

Association Rule Learning with Apriori.

A pipeline for market basket analysis aimed at identifying product associations to optimize retail promotions and bundle deals using SQLite, mlxtend & D3.js

In this section i will create a association rule learning recommender on the online_retail_ii dataset