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Projects

// selected work in data science & machine learning

Utilizing Pandas to Analyze "Friends" for a Reboot

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Exploratory and statistical analysis of the sitcom Friends to identify patterns in viewership, dialogue distribution, and emotional range to inform a potential reboot strategy.

// key outcomes
  • ›Analyzed episode-level data including directors, writers, and viewership trends
  • ›Applied hypothesis testing and regression analysis to examine IMDB ratings and audience patterns
  • ›Used NLP techniques to analyze dialogue distribution and generate episode titles in the style of the original show
PythonPandasNLPStatistical AnalysisRegression

Diabetes Risk Prediction Using Medical Records

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Built a logistic regression model to predict diabetes onset using medical record data, with a focus on data cleaning, visualization, and interpretability.

// key outcomes
  • ›Cleaned and preprocessed medical data by handling missing and invalid values
  • ›Visualized feature distributions and correlations using histograms and scatter plots
  • ›Achieved 75% accuracy on a held-out test dataset using logistic regression
PythonPandasScikit-learnMatplotlibLogistic Regression

Image Classification with CNNs on CIFAR-10

Collaborated on developing a convolutional neural network to classify images from the CIFAR-10 dataset, focusing on model optimization and performance evaluation.

// key outcomes
  • ›Implemented and trained a CNN using TensorFlow
  • ›Experimented with hyperparameters to optimize validation performance
  • ›Achieved 79.74% test accuracy on CIFAR-10 image classification
PythonTensorFlowCNNsMachine Learning