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Yueh-Han Chen's Projects

ab_testing icon ab_testing

Conducted A/B tests and regression analysis to examine the conversion rate difference between the control and experiment groups.

data-cleaning-assistant icon data-cleaning-assistant

Data Cleaning Assistant is a web application that uses OpenAI's GPT 3.5 model to suggest data cleaning tasks for a given dataset.

data-modeling-for-a-music-streaming-app icon data-modeling-for-a-music-streaming-app

Modeled the data with Python and Apache Cassandra, which enabled the analytics team to write queries and answer questions like “Give me every username who listened to a given song”

finding_donors_for_a_charity icon finding_donors_for_a_charity

Comparing Random Forest, Gradient Boosting, and XGBoost to select the best model to predict potential donors for a Charity.

identify-customer-segments icon identify-customer-segments

Unsupervised learning techniques to identify segments of the population that form the core customer base for a mail-order sales company in Germany

mall_customer_segmentation icon mall_customer_segmentation

Comparing KMeans, Hierarchical Clustering, and GMMs and selecting the best model to segment customer information using the Silhouette score.

marketing-job-market-analysis icon marketing-job-market-analysis

Used python(numpy, pandas, matplotib, and seaborn) to analyze the data from h1bdata.info to understand the situation of H1B for marketing jobs.

marketing_analytics icon marketing_analytics

Using Python to conduct EDA, perform statistical analysis, visualize insights, and present data-driven solutions to Chief Marketing Officer in the company

pisa-analysis icon pisa-analysis

Use Pandas, Matplotlib, and Seaborn to conduct exploratory data analysis by Univariate, Bivariate, and Multivariate visual exploration.

telco_customer_churn_analysis icon telco_customer_churn_analysis

Use Multiple Linear Regression, Python, Pandas, and Matplotlib to analyze the lifetime value and the key factors of the ‘Telco Customer Churn’ dataset.

trending-youtube-video-analysis icon trending-youtube-video-analysis

Use Python, Pandas, and Matplotlib to analyize “Trending YouTube Video Statistics”, including Data Assessing, Data Cleaning, EDA, Visualization and Drawing conclusion.

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