This repository contains introductory notebooks for association rules.

notebooks

3 notebooks covering Classification, Clustering Analysis and Frequent Pattern Mining in the scope of Data Mining lectures in Marmara University.

Script tersebut menerapkan kerangka kerja Knowledge Discovery in Database (KDD) yang mencakup data mining dengan metode algoritma FP-Growth untuk menemukan hubungan asosiasi antar item.

Collection of example Jupyter Notebooks and R Markdown files for predictive analytics

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.

Here I have provided some common algorithms used in big data, I've attached an HTML(Python), Python Notebook and R project for each demonstration

Here you will find a Notebook with examples of various Machine Learning algorithms (ML), more specifically, Supervised and Unsupervised Learning examples. All of the code is followed by explanations and everything is easy to use and to understand thanks to the documentation.

Contains the implementation of the Apriori Algorithm on French Retail Store dataset and the conclusion and suggestions to increase the profits from analysis.

The repository contains several Jupyter notebooks, each of which covers a different machine learning project, such as sentiment analysis, image classification, and customer segmentation. You also have code examples and datasets included to help users understand and implement the projects themselves.