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ads_teaching icon ads_teaching

Teaching repo for Applied Data Science @ Columbia, a project-based course for data science skills (statistical thinking, machine learning, data engineering, team work, presentation, endurance of frustration, etc).

label-noise-and-correction icon label-noise-and-correction

Project 3 responsible for project coding part, baseline model, Model I & II, also as presenter, make the PowerPoint. Mitigated noisy label in the CIFAR-10 dataset by developing Convolutional Neural Network (CNN) architectures and implementing extensive data augmentation to improve model robustness and generalization, resulting in accuracy to 74.4%

linear-regression icon linear-regression

Project 1 in Columbia University. Conducted a detailed linear regression study on cross-sectional dataand time-series data , employing methods like OLS/WLS for analytical insights.

red-bull-matches-analysis icon red-bull-matches-analysis

Part 1: Analyzing correlation with each variables that influence on NYRB’s match. Part 2: Analyzing the game content through on-field data.

shiny-app-development icon shiny-app-development

Project 2 in Columbia University. Created the baseline of the shiny app, defining the UI and the server along with the baseline for the visualizations Engineered a Shiny web application featuring heatmaps for visualizing disaster types and COVID -19 case distributions, enabling state specific and temporal data analysis.

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