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Machine Learning House Prediction project cover
Machine Learning Machine Learning House Prediction

Machine Learning

Machine Learning House Prediction

Built a neural-network model that grouped houses into price bands from their features.

The model helped sort properties into usable market categories.

PythonTensorFlowMachine LearningNeural Networks
Neural network Model
Classification Task
Market screening Use

Problem

What needed to be solved.

Property data is hard to scan quickly when the goal is to sort houses, not price every one by hand.

The model needed to turn feature patterns into clear price categories.

Approach

How the system was framed.

I treated it as a classification problem with a real use case: faster screening and better market grouping.

The work focused on making the model output easy to use in a property workflow.

Build Details

Architecture, tooling, and operating logic.

  • TensorFlow model experiments.
  • Feature-based classification setup.
  • Output shaped around price tiers.
  • Project write-up aimed at applied ML work.

Results

Operational outcome.

  • Added a clear machine learning project to the portfolio.
  • Showed model work tied to a practical decision task.
  • Expanded the project mix beyond automation and workflows.