Machine Learning Predictor for NBA games that takes into account player stats, team stats.
-
Updated
May 3, 2018 - Python
Machine Learning Predictor for NBA games that takes into account player stats, team stats.
NBA Shots visualization
🚄东方快车,🚄一带一路。分析财务产品盈亏报告、购物篮分析 https://gitee.com/englianhu
Basket-Sensitive Recommender System & Factorization Machines for grocery shopping based on hybrid random walk models.
Package for automating clustering (pipeline).
Machine Learning examples using basket analysis algorithm
Market basket analysis using mlxtend apriori algorithm and Echarts Visualization
This repository contains my code for a basket analysis study.
This Market Basket Analysis project in Python/R offers a versatile solution for uncovering purchasing patterns from transactional data. Utilizing powerful libraries like pandas, sqlalchemy, and mlxtend, it's ideal for businesses seeking to enhance marketing strategies and boost sales through data-driven insights.
Undergraduate Project - Association Rule (Basket) Analysis on 'Groceries' Data
market basket analysis implemented in R based on data from retail shops.
Data Mining and Machine learnining project to help prescribe the best lenses to a patient based on a variety of parameters, and classify mushrooms and edible or not. Also the extraction of data of an E-Commerce group.
Practicum 100 project: analyze the store's product range and identify patterns that could be used in marketing strategy for boosting profit and customer satisfaction
Define/record plays for Basket-Ball
Built a Gradient Boosting decision tree (LightGBM) Model to predict the customers next cart item using the customer’s previous purchase history.
This project is an Association Rule Mining implementation combining the Apriori algorithm with MapReduce that was implemented in the Masters of Advanced Analytics at Nova IMS
The goal is finding the relationship between web pages using Association Pathern Mining
A heavy and complete analysis for a distribution company that is selling plenty of products. This nice report contains various amazing analyses ranging from exploratory analysis, Basket and RFM analysis, and recommendations for the management to help them for decision making.
Add a description, image, and links to the basket-analysis topic page so that developers can more easily learn about it.
To associate your repository with the basket-analysis topic, visit your repo's landing page and select "manage topics."