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classifying_complaint_types

This project performs text classification on a dataset of complaints about traffic conditions to the city of Boston. You can find the data here: https://data.boston.gov/dataset/vision-zero-entry There are two goals: First, try to predict the type of complaint (“REQUESTTYPE”) from the complaint text. Second, try to come up with a better categorization of the data into semantic categories.

csds-material

Course material for the Computer Systems for Data Science class at Columbia

four-algorithms-from-scratch

Naive Bayes, KNN, Logistic Regression, Newton's Method from scratch in Python

homework-iii-apm-master

predicting_rent

A real estate agent wants to estimate the market rate for some apartments in NYC that just went into the market again. They want to use the data posted by the Census in 2014: https://www.census.gov/housing/nychvs/data/2014/userinfo2.html (The data is at https://www.census.gov/housing/nychvs/data/2014/uf_14_occ_web_b.txt) You can find a parsed version on figshare: https://ndownloader.figshare.com/files/7586326

predicting_subcribers

A banking institution ran a direct marketing campaign based on phone calls. Often, more than one contact to the same client was required, in order to assess if the product (bank term deposit) would be subscribed or not. This project predicts whether someone will subscribe to the term deposit or not based on the given information.

spoon-knife

This repo is for demonstration purposes only.