Part 1 – Further parts will be released in the future.
How has COVID-19 affected the New York City real estate market?
Our team at NJIT found several different insights that would be of use to investors, buyers/sellers, and lenders.
To check out how the sales price was affected by the building’s dimensions, location, and other quantitative/qualitative features, check out our the EDA here – https://github.com/Data-SR/real_estate/blob/main/EDA_tax_class_1.ipynb
The graph below shows a snippet from the EDA – this is how the sales price varied based on the different school districts in New York City. *See the EDA for the full graph*
For podcast fans and listeners, I’ve created a simple podcast recommendation algorithm based on user inputs and preferences.
This is based on the market basket analysis in data mining and was constructed using python. I used an Apriori algorithm with association rules to figure out the confidence, lift, and support variables.
Based on these variables, recommendations can be made to determine which podcasts you would enjoy.
Best part is – this can be done with very few lines of code.
You can check the code out here – https://www.kaggle.com/datasr/podcast-mining
Interested in football? Crazy about analytics? We combine both to develop a new way to measure the defensive success of NFL teams.
We entered the NFL Big Data 2021 and generated insights that help predict the defensive success rate of blitzes under various scenarios. The results that we generated are valuable to NFL teams to help them make in day coaching decisions and adjustments.