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Machine Learning by Using Regression Model

Machine Learning by Using Regression Model

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Machine Learning Explained

Machine Learning is the process of letting your machine use the data to learn the relationship between predictor variables and the target variable. It is one of the first steps toward becoming a data scientist.

There are two kinds of Machine Learning: supervised, and unsupervised learning....

  • Nominal: used for labelling variables(m- male and f- female)
  • Ordinal: used for measuring non-numeric with an order of the values(1-unhappy, 2-ok, 3- happy)
  • Data Cleaning: In this data set, there are 2051 rows with 80 colum...

In order to predict the outcome variable (y variable) you need to turn all the object type columns into numeric in order to predict the Sale Price. So first, I converted all the ordinal columns into numeric by assigning them by numbers, and for all the other features I created dummy variables.

After creating all the features to predict the sale prices, using sklearn, we train-test-split the training data. In Regression, there are a lot of models you can choose from to get the best performing model. In this project, I ran Linear Regression, Ridge, and Lasso models.

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