we're going to use information like a person's age, sex, BMI, no. of children and smoking habit to predict the price of yearly medical bills. This kind of model is useful for insurance companies to determine the yearly insurance premium for a person. The dataset for this problem is taken from: https://www.kaggle.com/mirichoi0218/insurance

We will create a model with the following steps:

Download and explore the dataset Prepare the dataset for training Create a linear regression model Train the model to fit the data Make predictions using the trained model

Built With

  • basics:
  • linear
  • logistic
  • minimal):
  • pytorch
  • regression
  • regression:
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