https://github.com/nikdata/portfolio

Data Science Portfolio
https://github.com/nikdata/portfolio

Last synced: 3 days ago
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Data Science Portfolio

• Host: GitHub
• URL: https://github.com/nikdata/portfolio
• Owner: nikdata
• Created: 2019-08-20T18:19:05.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-02-20T16:23:49.000Z (almost 3 years ago)
• Last Synced: 2024-11-09T07:38:38.924Z (about 2 months ago)
• Size: 6.85 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Nikhil's Portfolio

This repo holds project reports and my resume for my data science work.

- [Resume](https://github.com/nikdata/portfolio/tree/master/Resume) holds the latest copy of my resume in PDF format

- [Reports](https://github.com/nikdata/portfolio/tree/master/Reports) holds project reports for my academic work at Northwestern University.

---

Here's a brief summary of the projects:

- Wins per game predictive modeling for over 100 years of baseball data using regression and decision trees using *glm*, *caret*, *broom*.

- Wine case purchase volume predictive modeling using poisson, negative binomial, and hurdle models using *glm*, *caret*, *broom*

- Autocrashes predictive modeling using *ordinary least squares (OLS)*, *logistic regression* 

- Discrete choice experiment modeling using *Hierarchical Bayes Multinomial Logit* to select product design

- Model to predict target market for campaign using *random forests* and *naïve bayes* models

- Customer segmentation modeling using *hierarchical agglomerative clustering* and *k-means* followed by market segmentation profiling

- Time series forecasting for the DengAI, disease spread competition, models using *xts*, *forecast*, and *neural networks*

- Model to predict donation amounts for a not-for-profit marketing campaign using a variety of machine learning modeling approaches including *boosting*, *bagging*, *random forest*, and *PCR* using caret