Analyse customer segmentation, sentiment on product review, and built a product recommender system
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Updated
Jan 15, 2021 - Jupyter Notebook
Analyse customer segmentation, sentiment on product review, and built a product recommender system
Black Friday Sales Analysis explores customer demographics, purchasing behaviors, and product trends to uncover insights and patterns driving sales during Black Friday events.
Multivariate Time Series Classification for Human Activity Recognition with LSTM
Predicting whether users will click on a promotional email for laptops based on historical user data and browsing logs.
Customer journey analysis with PM4PY in Python.
Building a nearest-neighbor classifier to predict online shopping purchase completions based on user browsing behavior. The project uses a dataset of 12,000 sessions, analyzing features like pages visited, session duration, and bounce rates
This is a customer loyalty analysis based on historical purchase behavior in R language.
Analyze customer behavior using SQL and Python to extract insights on purchase patterns, sentiment analysis, and marketing effectiveness.
Customer Purchasing Behavior Analysis and Sales Prediction
This project explores customer behavior and sales trends to help this small restaurant thrive.
Predicts customer upgrade likelihood using logistic regression, random forest, and XGBoost. Features NLP techniques and memory optimization.
An interactive interface for performing CRUD operations (Create, Read, Update, Delete) on a MySQL database related to Zomato data.
Hotel Booking EDA Project -- Exploratory Data Analysis of hotel booking demand data (city & resort hotels) to uncover booking trends, cancellation behavior, customer preferences, and insights for hotel management.
This project utilizes machine learning to analyze and segment e-commerce customer behavior. It predicts purchases and clusters customers based on demographic data and product preferences, aiming to optimize marketing strategies and enhance customer satisfaction.
This repository contains Power BI projects showcasing data analysis and interactive dashboards. Each project includes detailed visualizations and insights on diverse topics such as loan analysis, sales performance, and customer behavior.
This project is focused on identifying key products that contribute significantly to revenue and analyzing customer purchase behavior
The "Store Sales Database" project analyzes 100K sales entries, leveraging Python, SQL, and Power BI to manage, analyze, and visualize store performance. It provides insights into sales trends, regional performance, and customer behavior through real-time analytics, detailed reporting, and dynamic dashboards to support data-driven decisions.
End-to-end SQL and Tableau analysis of real user engagement, subscriptions, and learning outcomes on an online education platform.
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