Chapter 1

Introduction to Data Science and Data Pre-Processing

Learning Objectives

By the end of this chapter, you will be able to:

  • Use various Python machine learning libraries
  • Handle missing data and deal with outliers
  • Perform data integration to bring together data from different sources
  • Perform data transformation to convert data into a machine-readable form
  • Scale data to avoid problems with values of different magnitudes
  • Split data into train and test datasets
  • Describe the different types of machine learning
  • Describe the different performance measures of a machine learning model

This chapter introduces data science and covers the various processes included in the building of machine learning models, with a particular focus on pre-processing. ...

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