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Scala: Guide for Data Science Professionals by Patrick R. Nicolas, Arun Manivannan, Pascal Bugnion

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Chapter 2. Hello World!

In the first chapter, you were acquainted with some rudimentary concepts regarding data processing, clustering, and classification. This chapter is dedicated to the creation and maintenance of a flexible end-to-end workflow to train and classify data. The first section of the chapter introduces a data-centric (functional) approach to create number-crunching applications.

You will learn how to:

  • Apply the concept of monadic design to create dynamic workflows
  • Leverage some of Scala's advanced functional features, such as dependency injection, to build portable computational workflows
  • Take into account the bias-variance trade-off in selecting a model
  • Overcome overfitting in modeling
  • Break down data into training, test, and validation ...

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