Portfolio

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Selected Project in Data Science and Machine Learning Project

Analyzing the Growth and Trends of Data Science Roles: A Comparative Study of Job Titles, Salaries, Country Classification, and Company Size

I investigate the evolving field of data science. Through a comprehensive examination, I explore the relationship between job titles and salaries, the impact of country classification on compensation, and the correlation between company size and average salary. By uncovering patterns and trends in these areas, I aim to provide valuable insights for professionals and organizations, facilitating informed decision-making regarding career paths, talent acquisition, and compensation strategies.

View code on Github

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Exploring the Gaming Industry: Game Series, Sales, Publishers, and Developers

The Game Publishing Insights Dashboard offers a comprehensive view of the game publishing industry. It features a collection of charts, including a horizontal bar chart displaying the distribution of games among different publishers, a chart showcasing the number of games published by each publisher, and a line chart illustrating the yearly trend of game releases. This interactive dashboard provides valuable insights into the game publishing landscape, enabling users to analyze publisher-game relationships, track publishing trends over time, and gain a deeper understanding of the industry’s dynamics.

View code on Github

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Machine Learning Project: Recommender System with Similarity Function

In this project, I created a content-based recommender system for films. It analyzes the content and characteristics of each film to identify similarities and patterns, generating personalized recommendations based on user preferences. By leveraging film features, the system curates a list of similar films, helping users discover movies aligned with their interests and tastes.

View code on Github

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Dentist Patient Visit Predictions

In this project, I developed a linear regression model to predict dentist visits based on sales data of sweet foods. By analyzing the correlations between sweet food consumption and dental visits, the model helps dental practices anticipate patient numbers and optimize resource planning. This data-driven approach improves the efficiency and effectiveness of dental care management.

View code on Github

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Prediction of User Visits Through the Promotional Banner Feature

In this project, I developed a machine learning model to predict user engagement with promotional banners on a new e-commerce website. By analyzing user behavior and leveraging existing data, the model provides valuable insights for optimizing marketing strategies and targeting potential customers more effectively. This data-driven solution enhances user engagement and improves the effectiveness of promotional efforts on the platform.

View code on Github

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Skill-Based Project

A selection of smaller projects demonstrating specific data science and ML skills

• Simple Recommender System
• Comparing 3 Different Machine Learning Model to Make Customer Churn Prediction

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