vjais Goto Github PK

dp-5

dp-7

energy-efficient-target-coverage-protocol

This research project was implemented during Internship.It involves developing a Target Coverage Protocol for maximizing coverage of target region using trust mechanism.

event-prediction

This project is about predicting events that happened in certain locations within 3 months.

hashing-1

hashing-2

heaps-1

infinity-vr

This project is an multi level immersive Virtual Reality game developed for CS491.The idea behind this project was to get experience creating virtual worlds for people to move around in and interact.The user should be able to move through a series of outdoor scenes,either by walking or teleporting in given space.Each scene is designed in a unique way that user experiences immersive effect.

intelligent-dictionary

leetcode-onsite-interview

linked-list-1

ms-apriori-algorithm

MS-Apriori Algorithm is a an extended version of the Apriori Algorithm. It solves the rare item problem faced while implementing the Apriori Algorithm.

productsuccessrecommendor

python-assignment

Python assignments based on database and linux commands.

stack-1

stack-2

stock-prediction-using-tensorflow

A timeseries prediction task to predict the future prices of a stock using tensorflow.

strings-1

trees-1

trees-3

trees-4

two-pointers-1

vjais

Config files for my GitHub profile.

vjais.github.io

zillow-s-home-value-prediction

Zestimate was created to give consumers as much information as possible about homes and the housing market, marking the first time consumers had access to this type of home value information at no cost. “Zestimates” are estimated home values based on 7.5 million statistical and machine learning models that analyze hundreds of data points on each property. And, by continually improving the median margin of error (from 14% at the onset to 5% today), Zillow has since become established as one of the largest, most trusted marketplaces for real estate information in the U.S. and a leading example of impactful machine learning. Zillow Prize, a competition with a one million dollar grand prize, is challenging the data science community to help push the accuracy of the Zestimate even further. Winning algorithms stand to impact the home values of 110M homes across the U.S. In this million-dollar competition, participants will develop an algorithm that makes predictions about the future sale prices of homes. The contest is structured into two rounds, the qualifying round which opens May 24, 2017 and the private round for the 100 top qualifying teams that opens on Feb 1st, 2018. In the qualifying round, you’ll be building a model to improve the Zestimate residual error. In the final round, you’ll build a home valuation algorithm from the ground up, using external data sources to help engineer new features that give your model an edge over the competition. Because real estate transaction data is public information, there will be a three-month sales tracking period after each competition round closes where your predictions will be evaluated against the actual sale prices of the homes. The final leaderboard won’t be revealed until the close of the sales tracking period.