A Challenge Project in a Boot-Camp to create a ML Model to predict the prices of houses in Boston Massachusetts from multiple parameters Using Multivariable Regression.
Building a Regression Model that can Provide a Home Price Estimate based on home's characteristics like:
- The number of rooms
- The distance to employment centres
- How rich or poor the area is
- How many students there are per teacher in local schools etc
⭐ Luckily we have got our Final Model's Accuracy a little good -->
• Accuracy on Training data : 79%
• Accuracy on Testing data : 74%
Reference:
This is a copy of UCI ML housing dataset. This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. You can find the original research paper here.