https://github.com/ramarav/house_price_prediction

Machine learning approach for house price prediction using tensorflow.
https://github.com/ramarav/house_price_prediction

jupyter-notebook jupyter-notebooks keras keras-models keras-neural-networks keras-tensorflow numpy python python-3 python3 tensorflow

Last synced: 2 days ago
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Machine learning approach for house price prediction using tensorflow.

• Host: GitHub
• URL: https://github.com/ramarav/house_price_prediction
• Owner: ramarav
• License: gpl-3.0
• Created: 2020-06-28T12:05:14.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-06-29T14:59:25.000Z (over 4 years ago)
• Last Synced: 2024-02-27T11:14:22.559Z (8 months ago)
• Topics: jupyter-notebook, jupyter-notebooks, keras, keras-models, keras-neural-networks, keras-tensorflow, numpy, python, python-3, python3, tensorflow
• Language: Python
• Homepage:
• Size: 15.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# House_price_prediction

Let us build a neural network that predicts the price of a house according to a simple formula.

House pricing is as follows :

50000 for house and 50000 extra for each bedroom.

Now 1 bedroom house costs 100000 and 2 bed room house costs 150000 etc.

Let us create a neural network that learns this relationship so that it would predict a 7 bedroom house as costing close to 400000 etc.

Your network might work better if you scale the house price down. You do not have to give the answer 400.

It might be better to create something that predicts the number 4, and then your answer is in the 'hundreds of thousands' etc.