Eashani Deorukhkar
I am a graduate student at Syracuse University pursuing an MS in Applied Data Science. I aspire to be a data scientist working to solve complex problems with data-driven solutions. You can take a look at some of my projects below!
Portfolio
Academic Projects:
San Francisco Crime Analysis
Analyzed the patterns in crimes occurring in the districts of San Francisco and tried to predict the category of the crime based on the location and time of day
May 2019
Microsoft Malware Prediction
Applied big data analytics to Microsoft’s malware data to determine the probability of malware on a computer.
May 2019
Analysis of home equity dataset
Determined whether an applicant defaults on a home loan based on factors like type of job, reason for loan. Calculated in Excel using the StatTools package
December 2018
Prediction of airline customer satisfaction
Analyzed survey data related to customer experience and flight information for various airlines and created predictive models using these factors to predict low satisfaction and suggested methods to mitigate it
December 2018
Carrier dome ticketing database
Created a mock ticketing database for Syracuse University’s Carrier Dome using SQL and PL-SQL
December 2018
Personal Projects:
Quality of Exercise Execution
Uses Machine Learning to determine the quality of physical exercise being done by an individual.
December 2017
Transmission and mileage- An analysis
Uses regression to determine the extent to which the transmission type affects the mileage of a car. Based on the mtcars dataset in R.
November 2017
Analysis of the ToothGrowth Dataset
Study of the ToothGrowth dataset available in R to determine the effect of type and dosage of supplements on tooth growth in rats using hypothesis testing.
October 2017
Central Limit Theorem using Exponential Distributions
Analyze a set of exponential distributions using R to show that the theorem holds true for the given distribution
October 2017
NOAA storm database exploration
Analyze U.S. National Oceanic and Atmospheric Administration's storm database. Uses R to answer questions about severe atmospheric events and their effect on human life and property
September 2017
Papers
Substance abuse prevalence study
Uses data analytics to determine correlation of substance abuse based on demographic parameters
Deorukhkar, Eashani and Ghosh, Shreyashi and Ghadge, Hemangi, “Prediction of the prevalence of substance abuse based on the demographic parameters of the individual,” International journal for scientific research and development, May 2017
May 2017
Google Cloud dataflow- An Insight
A review of Google's technology for stream and batch processing of data in the cloud.
Deorukhkar, Eashani, “Google Cloud Dataflow - An Insight” International journal of science and research, August 2017
August 2017
Education
Syracuse University
Master of Science - Applied Data Science
GPA: 3.6 / 4
August 2018 - May 2020
University of Mumbai
Bachelor of Engineering - Information Technology
GPA: 7.27 / 10
August 2013 - May 2017
Skills
Software & Tools
R Python SQL MongoDB HTML/CSS Excel APACHE SPARK MS OFFICE GOOGLE ANALYTICS MS POWER BI TABLEAU Ability to learn new things
Languages
-
English
-
Hindi
-
Marathi
-
Japanese
Certifications
-
AWS Certified Cloud Practitioner (June 2019 - June 2022)
-
Coursera Specialization "Data Science"
-
Japanese Language Proficiency Test level N2
-
Coursera Specialization "Deep Learning" - ongoing
San Francisco Crime Analysis
Analyzed the patterns in crimes occurring in the districts of San Francisco and tried to predict the category of the crime based on the location and time of day
Microsoft Malware Prediction
Applied big data analytics to Microsoft’s malware data to determine the probability of malware on a computer.
Analysis of home equity dataset
Determined whether an applicant defaults on a home loan based on factors like type of job, reason for loan. Calculated in Excel using the StatTools package
Prediction of airline customer satisfaction
Analyzed survey data related to customer experience and flight information for various airlines and created predictive models using these factors to predict low satisfaction and suggested methods to mitigate it
Carrier dome ticketing database
Created a mock ticketing database for Syracuse University’s Carrier Dome using SQL and PL-SQL
Quality of Exercise Execution
Uses Machine Learning to determine the quality of physical exercise being done by an individual.
Transmission and mileage- An analysis
Uses regression to determine the extent to which the transmission type affects the mileage of a car. Based on the mtcars dataset in R.
Analysis of the ToothGrowth Dataset
Study of the ToothGrowth dataset available in R to determine the effect of type and dosage of supplements on tooth growth in rats using hypothesis testing.
Central Limit Theorem using Exponential Distributions
Analyze a set of exponential distributions using R to show that the theorem holds true for the given distribution
NOAA storm database exploration
Analyze U.S. National Oceanic and Atmospheric Administration's storm database. Uses R to answer questions about severe atmospheric events and their effect on human life and property
Papers
Substance abuse prevalence study
Uses data analytics to determine correlation of substance abuse based on demographic parameters
Deorukhkar, Eashani and Ghosh, Shreyashi and Ghadge, Hemangi, “Prediction of the prevalence of substance abuse based on the demographic parameters of the individual,” International journal for scientific research and development, May 2017
Google Cloud dataflow- An Insight
A review of Google's technology for stream and batch processing of data in the cloud.
Deorukhkar, Eashani, “Google Cloud Dataflow - An Insight” International journal of science and research, August 2017
Education
Syracuse University
GPA: 3.6 / 4
University of Mumbai
GPA: 7.27 / 10
Skills
R Python SQL MongoDB HTML/CSS Excel APACHE SPARK MS OFFICE GOOGLE ANALYTICS MS POWER BI TABLEAU Ability to learn new things
- English
- Hindi
- Marathi
- Japanese
Certifications
- AWS Certified Cloud Practitioner (June 2019 - June 2022)
- Coursera Specialization "Data Science"
- Japanese Language Proficiency Test level N2
- Coursera Specialization "Deep Learning" - ongoing