Join our book community on Discord
https://packt.link/EarlyAccessCommunity
It’s hard to believe that the scikit-learn project started back in 2007 and officially launched in 2009. Even after so many years, it is hard to deny the impact the Python library has had on the world of data science and machine learning (ML). For many of us, scikit-learn is one of the first libraries we hear about when beginning our journey in ML programming and engineering – and that hasn’t changed as the library is one of the most widely used in research, academia, and production applications at scale in the business world.
This chapter will cover the standard conventions and core API elements of scikit-learn, including the design principles behind estimators, transformers, and pipelines, as well as common methods like fit(), predict(), and transform(). The exercises found throughout the rest of the book will involve using these conventions to build and evaluate models, focusing on understanding...
