rudrakshsyal Goto Github PK
Name: Rudraksh Syal
Type: User
Bio: Currently pursuing my double Master's in Business Analytics from Purdue University, I have graduated from BITS Pilani, India with Master's in Mathematics.
Location: Chicago, Illinois
Rudraksh Syal's Projects
airbnb-rating-system---emotional-or-rational
As a customer or a potential investor who lists properties on Airbnb, one would always be interested in determining the quality of the listing. The rating score is one of the indicators which every stakeholder looks forward to, in order to gauge this metric. It is often observed that this is not an accurate indicator.
amazon-auto-parts-textual-analysis-with--rshiny-web-application
We employ a text content analysis framework that has been successful in other studies to identify important features of automobile service parts
churn_prediction_ml_model
Regression Model Run for the processed data, along with measuring the accuracy parameters like Sensitivity, Specificity, etc. with summary sheet included.
churn_prediction_v1
Preprocessing and readying the leads data to input in the Machine Learning model.
craigslist-job-listing-transformation-via-text-modeling
Improved quality and presentation of job listings on Craigslist website via scraping and training data from Indeed’s job listings’, to enhance user experience, drive more traffic and thus increase revenue
dashboards_sql_analytics
Automated Dashboards, fetching the data via SQL queries and user-interface being MS Excel.
platform_conversionpercentage
To gauge platform conversion% across pages of the website, doctor attributes, and doctor rank on the website.
purdue_r_datamining_project
Academic Project for R & Data Mining Courses
shinyapps_in_rstudio
An automated, real-time web application covering important metrics of Product, such as monthly active users, liquidity, transactional value, etc.
text_mining_v1
Basics of 'Text Mining' in R, with data clean-up, plots, word-clouds, clustering and dendrograms.
text_mining_v2
Edit-distance algorithm for text-processing and scoring for each sentiment (+1, 0, -1).
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