Biography
Dr. Prithviraj Lakkakula is currently a Data Scientist at Mann+Hummel USA Inc., a global leader in filtration. Dr. Lakkakula has over seven years of experience in Data Analytics, specifically working on topics of time series analysis, demand & price analysis, and causal inference. Dr. Lakkakula is passionate about automation and gaining insights from data by applying statistics, machine learning, deep learning, and several other data science techniques.
- Applied Econometrics/Statistics
- Machine Learning
- Deep Learning
PhD in Applied Economics (Food and Resource Economics), 2014
University of Florida
M.S. in Applied Economics (Agricultural Economics), 2010
University of Arkansas
Skills
Experience
Blogs
Using Deep Learning for Predicting Soybean Disease
In this external project, I will demonstrate image analysis using deep learning for predicting soybean disease.
Classification: Predicting Wheat Variety Using Ensemble Models
Predict wheat variety accurately using multiple features employing two popular ensemble models, including random forest and gradient boosting model accounting for multicollinearity and hyperparameter tuning.
Shiny Web Application Showing Market Trends of Major Commodities in Agriculturally Important Countries
Interactive Shiny Web Application Showing Market Trends of Three Commodities in Five Coutries
Scalable Faceting with TrelliscopeJS
A demonstration of scalable faceting using ggplot2 and TrelliscopeJS R pacakges.
What is Big Data in the Context of Agriculture?
Spotlight on Economics post at NDSU on Big Data in Agriculture.