This project is focused on identifying key products that contribute significantly to revenue and analyzing customer purchase behavior

Predicts customer upgrade likelihood using logistic regression, random forest, and XGBoost. Features NLP techniques and memory optimization.

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 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.

Analysis customer behavior in a movie center

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

Performed Consumer Behavior Analysis using Google Trends for the word Tyson Chicken, and providing recommendations

Utilized BeautifulSoup to webscrape data and gain company insights. Also applied Random Forest algorithm to predict customer buying behaviour.

Analyzing customer interactions, purchases, and engagement on an e-commerce website 💡

Intelligent Algorithms website

With SQL queries I explore the Sakila DVD Rental database, to present insights about customer behavior and rental patterns.

Customer journey analysis with PM4PY in Python.

Multivariate Time Series Classification for Human Activity Recognition with LSTM

Modelling customers' behaviour for better marketing strategies. Constructing the baseline behavioural scorecard model to fasten the mortgage application process. In cooperation with Atom Bank.

Analyse customer segmentation, sentiment on product review, and built a product recommender system

This is a customer loyalty analysis based on historical purchase behavior in R language.

Literature Survey, Documentation, Analysis and Results