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2019_fall_assignment2

assignment-1-programming-introduction

assignment_lookandfeel

datamining

digital-marketing

Used data mining techniques such as boosted decision tree and neural networks to predicted if the customers receiving emails and phone calls as part of the marketing campaign will visit the store. Skills acquired: Tableau, SAS, Azure ML, Data Mining

digitalregistry

marketing-analytics

Marketing Data Analytics: Market Sensitivity using Conjoint Analysis. We used conjoint analysis to hone the product configuration that will maximize the market share of the product (product is Laptops). We also determined the market sensitivity of consumers and businesses, and researched the market situation using market simulation in XLSTAT

py

Repository to store sample python programs for python learning

s-p500-stocks-analysis-and-prediction

text-analytics-of-legal-documents

Unsupervised clustering techniques to cluster legal-summary documents. In legal cases, the arguments and case points are often constructed referring to past cases. This is a very common task that paralegals carry out today by manually browsing through thousands of reports to find relevant legal case reports so as to cite from them. Our goal is to provide with segmented documents by types of cases so that the paralegals has one less task in their hand. The project includes collating legal summary from 3890 documents, cleaning and preprocessing the text, converting text into vector form to use it with different clustering algorithms and coming up with clustered documents.

webscrapping-using-beautifulsoup-python

Used Beautiful Soup for webscrapping cars.com

yelp-academic-dataset-analysis

Perform Analysis on Yelp Academic Dataset, Perform Visualization, Graph Mining and create graphs on Yelp data, Model the data with various techniques and interpret the output, To perform sentiment analysis on Review dataset of Yelp