atnamin Goto Github PK

deep-learning

income-level-prediction

k-means

KMeans Clustering is used to cluster Universities into to two groups, Private and Public.

nlp

In this NLP project I attempted to classify Yelp Reviews into 1 star or 5 star categories based off the text content in the reviews. I used the Yelp Review Data Set from Kaggle. Each observation in this dataset is a review of a particular business by a particular user. The "stars" column is the number of stars (1 through 5) assigned by the reviewer to the business. (Higher stars is better.) The "cool" column is the number of "cool" votes this review received from other Yelp users. All reviews start with 0 "cool" votes, and there is no limit to how many "cool" votes a review can receive. In other words, it is a rating of the review itself, not a rating of the business. The "useful" and "funny" columns are similar to the "cool" column.

pca

random-forest-project

Publicly available data from lendingclub.com is explored to predict people with a profile with high probability to pay back the loans. We used Random Forest Classifier on lending data from 2007-2010 and tried to classify and predict whether or not the borrower paid back their loan in full.

stresswatch

svm

I analyzed the famous iris data set. The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by Sir Ronald Fisher in the 1936 as an example of discriminant analysis. The data set consists of 50 samples from each of three species of Iris (Iris setosa, Iris virginica and Iris versicolor), so 150 total samples. Four features were measured from each sample:the length and the width of the sepals and petals, in centimeters.