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.
