In the competitive airline industry, British Airways prioritizes customer satisfaction, utilizing sentiment analysis to evaluate passenger feedback from Airlinequality.com. This project categorizes sentiments and identifies key themes within reviews, enabling the airline to pinpoint improvement areas. 

BeautifulSoup, Pandas, TextBlob NaiveBayesClassifier, NLTK, re (Regular Expressions), Matplotlib

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Lanaguage: Python, Platform: Google Colab

The project aims to detect fraudulent transactions using various machine learning models such as Logistic Regression, Random Forest, and Neural Networks. By analyzing transaction data, the goal is to enhance the detection of fraudulent activity while minimizing false positives, ultimately providing insights that can improve fraud prevention strategies for financial institutions.

Pandas, Scikit-learn, TensorFlow, Matplotlib, Seaborn​

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Language: Python, Platform: GitHub

The analysis utilizes machine learning techniques such as LSTM Neural Networks and ARIMA models to predict the metastatic diagnosis period for breast cancer patients. The dataset explores the relationships between environmental conditions and health outcomes.This predictive insight is aimed at enhancing patient care by identifying patterns that could lead to earlier diagnosis and better-targeted interventions.

Pandas, TensorFlow, Scikit-learn, Statsmodels, Matplotlib

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Language: Python, Platform: GitHub

This project conducts A/B testing to evaluate the effectiveness of a new strategy on user engagement metrics. Analyzed the effectiveness of implementing a minimum order amount for free shipping in a B2B e-commerce setting. This analysis involved hypothesis testing to assess the impact on customer ordering behavior, providing actionable insights to enhance pricing strategies and increase customer retention.

Pandas, SciPy, Matplotlib, Statsmodels

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Language: Python, Platform: GitHub

The analysis involves the application of cluster analysis techniques such as K-means clustreing and Hierarchical clustering to customer survey data to identify distinct segments that exhibit unique characteristics and preferences. This strategic insight is aimed at optimizing Sticks Kebob Shop's expansion by targeting customer segments.

Tidyverse, Cluster, Factoextra, Ggplot2

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Language: R, Platform: Github

This study targets the hospitality industry's challenge of booking cancellations, aiming to mitigate their impact on revenue and operations. By developing a predictive model using extensive hotel booking data, we seek to improve forecasting accuracy, aiding strategic decision-making.

DPLYR, Ggplot2, MASS, RandomForest, GBM, Glmnet, Caret, pROC, PerformanceEstimation, Boot

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Language: R, Platform: Github

In this interactive dashboard, we delve into the dynamics of King County's housing market, presenting an in-depth analysis of property values across various neighborhoods.

It showcases key indicators such as average house prices, distribution by house features, and a geographical representation of market activity. Designed for potential homebuyers and real estate enthusiasts, the dashboard offers insightful trends and patterns, enabling data-driven decision-making in the property domain.

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Platform: Tableau

In the competitive airline industry, British Airways prioritizes customer satisfaction, utilizing sentiment analysis to evaluate passenger feedback from Airlinequality.com. This project categorizes sentiments and identifies key themes within reviews, enabling the airline to pinpoint improvement areas. 

BeautifulSoup, Pandas, TextBlob NaiveBayesClassifier, NLTK, re (Regular Expressions), Matplotlib

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Language: Julia