AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
🔨 Python implementation of FP Growth algorithm, new and simple!
Python project for Market Basket Analysis. Generates synthetic retail transactions, mines frequent itemsets using Apriori & FP-Growth, derives association rules, and outputs CSVs + visualizations. Portfolio-ready example demonstrating data science methods for uncovering product co-purchase patterns.
Implementation of FPTree-Growth and Apriori-Algorithm for finding frequent patterns in Transactional Database.
《大数据挖掘技术》@复旦 课程项目，试图从搜狗实验室用户查询日志数据（2008）中找出搜索记录中有较高支持度关键词的频繁二项集。在实现层面上，我搭建了一个由五台服务器组成的微型 Hadoop 集群，并且用 Python 实现了 Parallel FP-Growth 算法中的三个 MapReduce 过程。
Data Mining algorithms for IDMW632C course at IIIT Allahabad, 6th semester
Machine learning examples tested on Google Colab in Python3 for learning and practice. Updated once a week.
基于Python的 apriori，FP tree fp growth算法实现及求其强关系
Using Apriori algorithm to find frequent patterns in data created by "IBM Quest Synthetic Data Generator".
《机器学习实战》代码和数据。The code and data of Machine Learning in Action.
This project presents a data warehouse and mining system for retail transaction analysis using association rule mining
Analysis of sales transaction data to identify relationships between products (ice cream and drinks) using Association Learning with FP-Growth algorithm
Generate FP-Growth Tree of a dataset with visualized graph output.
Python Implementation of data mining algorithms(Apriori, Eclact, FP Growth ).
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