Pinned Repositories
insurance
working with insurance datset
Analytics-and-Data-Visualization-of-baby-name-in-New-York-City
This study includes Analytics and Data Visualization of baby name and birth in New York City, which describes the different visualization on the basis of baby name, county, and gender.
Hadoop-Big-Data-Tools
Hadoop, Mapreduce, Hive, Pig, Spark, Documentation and Assignments
insurance
working with insurance datset
Performance-evaluation-of-sequential-and-parallel-approach-to-optimize-quick-sort
Algorithm Parallelization: To find out an easy to implement yet efficient approach to parallelize quick sort
RISK-PREDICTION-OF-COLLISIONS-IN-TORONTO
Machine Learning Prediction and Classification Major Research Project: In this study, the Decision Tree, Random Forest and ARIMA time series model are implemented and analyzed over the Killed or Seriously Injured (KSI) Traffic Data so as to predict the severity of injury type, number of collisions in Toronto for future 12 months.
Social-Media-Topic-Mining
Topic Mining: Twitter data of Honda and Toyota
Voluntary-Retirement-Prediction-of-Employees
Prediction of employee turnover in a company which indicates how many employee are going to take voluntary retirement in next.
shailendra-yadav's Repositories
shailendra-yadav/Analytics-and-Data-Visualization-of-baby-name-in-New-York-City
This study includes Analytics and Data Visualization of baby name and birth in New York City, which describes the different visualization on the basis of baby name, county, and gender.
shailendra-yadav/Hadoop-Big-Data-Tools
Hadoop, Mapreduce, Hive, Pig, Spark, Documentation and Assignments
shailendra-yadav/insurance
working with insurance datset
shailendra-yadav/Performance-evaluation-of-sequential-and-parallel-approach-to-optimize-quick-sort
Algorithm Parallelization: To find out an easy to implement yet efficient approach to parallelize quick sort
shailendra-yadav/RISK-PREDICTION-OF-COLLISIONS-IN-TORONTO
Machine Learning Prediction and Classification Major Research Project: In this study, the Decision Tree, Random Forest and ARIMA time series model are implemented and analyzed over the Killed or Seriously Injured (KSI) Traffic Data so as to predict the severity of injury type, number of collisions in Toronto for future 12 months.
shailendra-yadav/Social-Media-Topic-Mining
Topic Mining: Twitter data of Honda and Toyota
shailendra-yadav/Voluntary-Retirement-Prediction-of-Employees
Prediction of employee turnover in a company which indicates how many employee are going to take voluntary retirement in next.