kaggle:Two Sigma Connect: Rental Listing Inquiries--top1

For the Two Sigma Connect: Rental Listing Inquiries dataset

Two Sigma Connect: Rental Listing Inquiries

[CMPT 459 Special Topics in Database Systems: Data Mining] A data mining/machine learning project aimed to recommend features to renters to attract more people to their listings on RentHop website. Use SVM, RandomForest, Logistic-Regression, KNN, Decision Tree, and Naive Bayes.

Two Sigma Connect: Rental Listing Inquiries competition

Two Sigma Connect: Rental Listing Inquiries

Two Sigma Connect: Rental Listing Inquiries

Two Sigma Connect: Rental Listing Inquiries

Recruiting level Kaggle competition by Two Sigma featuring rental listing data from RentHop. The objective was to predict the number of inquiries a new listing receives based on the listing’s creation date and other features. The data came from renthop.com, an apartment listing website.

Two Sigma Connect: Rental Listing Inquiries ( https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries )

Predicting the Interest Level Renthop listing

Text Mining basics in practice

Kaggle Two-Sigma-Connect-Rental-Listing-Inquiries

Two Sigma and RentHop, a portfolio company of Two Sigma Ventures, invited Kagglers to unleash their creative engines to uncover business value in this unique recruiting competition. RentHop makes apartment search smarter by using data to sort rental listings by quality. But while looking for the perfect apartment is difficult enough, structuring and making sense of all available real estate data programmatically is even harder. Two Sigma invited kagglers to apply their talents in this recruiting competition featuring rental listing data from RentHop. Kagglers will predict the number of inquiries a new listing receives based on the listing’s creation date and other features. Doing so will help RentHop better handle fraud control, identify potential listing quality issues, and allow owners and agents to better understand renters’ needs and preferences. Two Sigma has been at the forefront of applying technology and data science to financial forecasts. While their pioneering advances in big data, AI, and machine learning in the financial world have been pushing the industry forward, as with all other scientific progress, they are driven to make continual progress. This challenge is an opportunity for competitors to gain a sneak peek into Two Sigma's data science work outside of finance.

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Two Sigma Connect: Rental Listing Inquiries with R. Json to csv transformation.

How much interest will a new rental listing on RentHop receive?

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Project from Kaggle (https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries)

Kaggle上很好的一个分类项目

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Data analysis, Machine learning, multiclass label

Kaggle: Two Sigma Connect: Rental Listing Inquiries

Code for the Kaggle Two Sigma Connect Rental Listing Inquiries

Тестовое задание в ЦФТ

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Kaggle competition - Two Sigma Connect: Rental Listing Inquiries (https://www.kaggle.com/c/two-sigma-connect-rental-listing-inquiries)

Forecasting in R

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Finding the perfect place to call your new home should be more than browsing through endless listings. RentHop makes apartment search smarter by using data to sort rental listings by quality. But while looking for the perfect apartment is difficult enough, structuring and making sense of all available real estate data programmatically is even harder. Two Sigma and RentHop, a portfolio company of Two Sigma Ventures, invite Kagglers to unleash their creative engines to uncover business value in this unique recruiting competition.