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
Multivariate Time Series Classification for Human Activity Recognition with LSTM
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.
Customer Purchasing Behavior Analysis and Sales Prediction
Predicts customer upgrade likelihood using logistic regression, random forest, and XGBoost. Features NLP techniques and memory optimization.
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.
Detailed analysis of a company’s ideal customers, helps a business to better understand its customers and makes it easier for them to modify products according to the specific needs, behaviors and concerns of different types of customers
This project is focused on identifying key products that contribute significantly to revenue and analyzing customer purchase behavior
Modelling customers' behaviour for better marketing strategies. Constructing the baseline behavioural scorecard model to fasten the mortgage application process. In cooperation with Atom Bank.
Cab Investment Strategy in the US examines market trends, customer demographics, and profitability for Pink Cab and Yellow Cab, offering insights to guide strategic investment decisions through data analysis, visualizations, and forecasting.
Literature Survey, Documentation, Analysis and Results
Intelligent Algorithms website
With SQL queries I explore the Sakila DVD Rental database, to present insights about customer behavior and rental patterns.
Analyzing customer interactions, purchases, and engagement on an e-commerce website 💡
Recommendation system using ML
Analysis customer behavior in a movie center
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