House hunting - the data scientist way

Buying a house is a huge financial and personal undertaking for most people. Whether we realize or not, a lot of decisions we make are heavily influenced by the location of the houses. In this talk, I show how Python's data analysis and geospatial analysis packages can be used to analyze the whole gamut of available listings in a market, evaluate and score properties based on various attribute and spatial parameters and arrive at a shortlist. I extend by showing how this process can be used to build a machine learning model that will understand our preferences and continue to learn as more data is fed. I conclude with ideas for future work and how rest of the industry is progressing in this field.

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