Abhay Goyal
Bio
I’m currently a Master’s student in the Computer Science Department at Stony Brook University. My focus areas are Data Science, Data Analytics, Machine Learning and Data Engineering. I am actively looking for internship opportunities in the same.
I have worked on AMES Housing, IEEE Fraud Detection projects which can be seen from my resume here. These projects have given me a basic insight into the world of drawing insights to drive businesses and understand the needs of the company.
Education
Degree | Major | University | Year |
---|---|---|---|
Grad | Computer Science | Stony Brook University | 2019-21 |
Undergrad | Computer Science | SRM Institute of Science and Technology | 2015-19 |
Contact
- Linkedin: /abhay-goyal-at-work
- github: AbhayGoyal
- Kaggle: /AbhayGoyal
Relevant Coursework
Data Science Fundamentals, Probability and Statistics for Data Science, Visualization, Machine Learning, Databases
Tableau Work :- here
Ongoing Projects
Dashboard using D3.js
- To visualize and understand the adoption of DS and ML methods of organizations and individuals using the ML & DS Survey 2019 done by Kaggle.com
Ongoing Research under Prof. Christian Luhmann
Objective :- To understand the flow of false memory and how collective memory plays a role in this. Progress : -In this we are starting with understanding how collective memory work. We are currently trying to replicate the working on this paper and using our own metrics of recall and inhibition to show the flow of collective memory. Next we plan to also incorporate the literature on false memory and how can it infect and flow in collective memory.
Personal Projects
- Retail Sales Analysis
- To perform descriptive analytics and models to increase sales.
- AMES Housing Project
- Analysed and understood the factors affecting house prices and made model to predict them.
- IEEE Fraud Detection
- Analysed and did in depth analysis of frauds, how do they occur and when
- Bank Marketing
- Analysed to predict(using Logistic Regression, Random Forest) what policies would people take based on features such as did, what they tak last time, salary, housing etc
- HR Analytics
- Did some basic visualizations do understand the satisfaction level of employees, used linear regression to predict it.