Stevens Institute of Technology
INVENTORY MANAGEMENT SYSTEM IN MS EXCEL
I have developed an inventory management system in Excel where I have created a form to enter details of items.
For this project I used MS Excel functions such as pivot table, IF, SUMIF, COUNTIF, VLOOKUP, HLOOKUP, HYPERLINK and many more complex functions.
I am writing a blog on this project where you will get more details.
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NETWORK OPTIMIZATION MODEL FOR LOGISTICS COMPANY STATIONARY DEMAND
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DECISION SUPPORT SYSTEM FOR CHOOSING BEST CAR USING EXCEL
1. Choosing a car can be a very subjective task. We need to decide which company best suits our Price range, Fuel Efficiency, Resale value etc
2. I and my group mates developed user interface model in MS Excel using risk mitigation tools like Monte Carlo simulation
3. Build recommendation system filtering car models from 96 cars using MAUT Model
NJ TRANSIT TRAIN DELAY ANALYSIS USING PYTHON
1. Performed complex statistical analysis and exploratory analysis and modeling on big dataset using python libraries
2. Developed python code for analyzing delays of trains and forecasted delays for few months
3. Focussed on getting the insights from data of NJ transit trains from March 2018 to march 2019
4. NJ Transit is used by most of the New Jersey Commuters and so NJ Transit has to maintain their train schedules on time
IMPACT OF AUTONOMOUS VEHICLES ON NEW YORK DEPARTMENT OF TRANSPORTATION
Project aimed to study effects of a transportation system on NY Department of Transportation with 50% Autonomous Vehicles.
Following categories were taken into consideration:
1. Vehicle miles traveled and safety
2. Public transit and freight flow
3. Infrastructure design and investment decisions
4. Social/equity issues and state’s economy
From this assessment, we will make management and policy recommendations for the transportation system which will help them to decide whether to implement this project as it involve lots of financial support
INSURANCE COMPANY PREDICTIVE ANALYSIS USING PYTHON
This project focusses on predictive analysis and visualization of age of customers according to their BMI, charges paid for their insurance. In addition how age of customer differ in insurance policy price structure, how anyone smoking has more price for their policy. Got 86% hyper-parameter optimization for training data.