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In linear regression, regularization is a process of making the model more regular or simpler by shrinking the model coefficient to be closer to zero or absolute, ultimately to address over fitting.

data-analysis data-science machine-learning mean-absolute-error mean-absolute-percentage-error regularization-methods regularized-linear-regression root-mean-square-error

regularized-regression_predicting-housing-price's Introduction

Hi 👋 I am Camytha,

I am a BSMEE graduate from University of Arizona and Sampoerna University.

  • 📫 Currently, I graduate from a data science bootcamp at dibimbing.id. I learn about data type and structure, statistics, data cleaning, data manipulation, data visualization, Exploratory Data Analysis (EDA), regression, supervised and unsupervised machine learning, hyperparameter tunning, etc.
  • ✨ I often use Rstudio and Google Colaboratory as my tools to manage and analyze data (R and Python languages)
  • 💞️ I am best reached at www.linkedin.com/in/camytha-octanuryati-rochmad/

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