Top 5 Amazon Sales Dashboard Trends & Insights for 2026
amazon-dataset 开源项目推荐(41 个)
amazon-dataset 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 41 个仓库A dataset sample of the most reviewed and best-selling books on Amazon
This is our implementation for our paper: TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation
通过排名第一的亚马逊爬取 API 提取数据,包括搜索结果、产品详情、优惠信息、评论、问答、畅销商品和卖家信息。立即开始您的免费试用!
Free Trial with the #1 Amazon Scraper API, including search results, product details, offers, reviews, Q&A, bestsellers, and seller information.
Sentiment analysis on product reviews with identification of most reviewed products from Amazon product reviews dataset consists of 35000 reviews.
Data Visualization and Data Analytics with Tableau by solving real data analytics problems
This code explains how to perform (Exploratory Data Analysis) EDA using python on the amazon Alexa dataset.
Comprehensive Amazon sales dashboard analyzing $2.18M+ in sales data with interactive visualizations for revenue tracking, product category performance, and business intelligence insights. Features monthly sales trends, top-performing products, and regional analytics.
This repository contains data related to Amazon UK sales from 2018 to 2021
A notebook to analyze Amazon Recommendation Review Dataset.
EDA on Amazon Data of a few million customers & then building a CNN Deep Learning Model.
Exploratory analysis of 1,000+ Amazon products, focusing on pricing, ratings, reviews, and customer behavior. Includes visualizations, sentiment insights, and key patterns across product categories to support data-driven strategies.
This Capstone Project summarizes our preliminary (Exploratory Data Analysis EDA) analysis on the dataset, the Black Friday Dataset from Amazon. It shared some insightful results from the EDA and descriptive statistics. Further, this paper identifies a set of analyses used to answer the business questions on the dataset and justifies those findings.
Knowledge-Aware Graph Prompt Tuning for Cross-Domain Recommendation
MIT Applied AI & Data Science Program Elective Project. End-to-end recommendation system project using Amazon product ratings data, implementing rank-based, collaborative filtering (User-User, Item-Item), and SVD models, with evaluation and visual analysis.
Amazon purchases dataset analysis and exploration — Great Learning internship exercise
This project has analyzed the Amazon Review dataset to find any motivating insight concerning heterogeneous recommendations and answer the following questions: • Which users reviewed products from several domains? • What are the pairs of domains connected via bridge users? • What is the relation between domains? • What is the accuracy of using a…
A session-based recommendation system to recommend baby products on Amazon using 4 models namely ITEMKNN, POP, GRU4Rec, and STAMP, STAMP performs the best in all accuracy metrics followed by GRU4Rec. We also did result analysis, including ranking accuracy, coverage, popularity.
Product recommendation system using SVD and the Amazon Electronics Reviews dataset.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/amazon-dataset。
- 该话题在 GitHub 上共有 41 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 261 Star,覆盖 4 种主要语言,数据更新于 2026-11-07。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。