House Price Prediction(Regression) with Tensorflow - Keras
Tensorflow and Keras
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
Keras is an open-source neural-network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, or PlaidML. Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible.
Dataset
The data contains information from the 1990 California census. The columns are as follows:
longitude: A measure of how far west a house is; a higher value is farther west
latitude: A measure of how far north a house is; a higher value is farther north
housingMedianAge: Median age of a house within a block; a lower number is a newer building
totalRooms: Total number of rooms within a block
totalBedrooms: Total number of bedrooms within a block
population: Total number of people residing within a block
households: Total number of households, a group of people residing within a home unit, for a block
medianIncome: Median income for households within a block of houses (measured in tens of thousands of US Dollars)
medianHouseValue: Median house value for households within a block (measured in US Dollars)
oceanProximity: Location of the house w.r.t ocean/sea
Data Source: California Housing Prices Dataset