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Monica Phan

monica-phan26

Background in retail and planning, a data practitioner but not satisfied enough with Excel, pursuing becoming a data problem solver with Data Science skills.

Data
New Jersey

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Repositories

12
MO
monica-phan26/STA9750-2026-SPRING

STA 9750 - Software Tools for Data Analysis - Project folder

R00Updated 5 days ago
MO
monica-phan26/monica-phan26.github.io

No description provided.

00Updated 1 month ago
MO
monica-phan26/Microsoft-new-movie-studio-recommendationsFork

Analyzed data on 200+ studios and 3000+ movies to advise Microsoft on investing in a new movie studio. Recommended Animation genre with a budget of 50-200M USD to double ROI, and managed popularity of 20+ to ensure global revenue greater than 500M USD.

Jupyter Notebook00Updated 2 years ago
edaexploratory-data-analysispython
MO
monica-phan26/Proposal_for_image_search_feature_for_NITA_fashion_ecommerce_company

Implemented an image search feature on the website to improve the experience of 35% of customers dissatisfied with keyword searches. This enhancement incorporated the CNN model with 95% accuracy for image classification and the Siamese model for the top 5 similar products, leveraging the data set of 24,000+ images across 10 different classes.

Jupyter Notebook00Updated 2 years ago
cnndatadata-augmentationdata-projectsdata-sciencedeep-learninge-commerceimageimage-classificationimagesimilaritymobilenetv2resnet50siamese-neural-networksimilarity-searchtransfer-learningvgg16-model
MO
monica-phan26/Walmart-weekly-sales-forecast-tool

Generated automated weekly sales forecast by departments in 45 stores using a dataset of weekly sales data spanning over 2 years, by employing the Random Forest Regressor model with achieving the Mean Absolute Error (MAE) of less than 10% of the forecast.

Jupyter Notebook00Updated 2 years ago
arimadata-analysispythonrandomforestregressorsaritime-series
MO
monica-phan26/Syria-Tel-customer-churn-alerts

Reduced the initial churn rate from 25% to less than 20% by implementing churn-prevention alerts based on the predictions of customer churn likelihood built from the XGBoost classification model with 95% accuracy from a 6-month subscriber dataset.

Jupyter Notebook00Updated 2 years ago
machine-learningpredictive-modelingpythonxgboost-classifier
MO
monica-phan26/King-County-house-pricing-predictionFork

Developed a housing price prediction tool for the real estate company to forecast upcoming housing prices by employing a linear regression model with an R-squared value of 70% based on a 13-month dataset of King County residences.

00Updated 2 years ago
linear-regressionpredictive-modelingpython
MO
monica-phan26/stablediffusionFork

High-Resolution Image Synthesis with Latent Diffusion Models

00Updated 2 years ago
MO
monica-phan26/mlflowFork

Open source platform for the machine learning lifecycle

00Updated 2 years ago
MO
monica-phan26/Kera_NLPFork

No description provided.

00Updated 2 years ago
MO
monica-phan26/PlantLeaf_ClassificationFork

No description provided.

00Updated 3 years ago
MO
monica-phan26/NYC_DS_042423Fork

NYC Data Science April 24 Cohort

Jupyter Notebook00Updated 2 years ago

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