Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Modern Scala Projects
  • Toc
  • feedback
Modern Scala Projects

Modern Scala Projects

By : gurusamy
close
Modern Scala Projects

Modern Scala Projects

By: gurusamy

Overview of this book

Scala is both a functional programming and object-oriented programming language designed to express common programming patterns in a concise, readable, and type-safe way. Complete with step-by-step instructions, Modern Scala Projects will guide you in exploring Scala capabilities and learning best practices. Along the way, you'll build applications for professional contexts while understanding the core tasks and components. You’ll begin with a project for predicting the class of a flower by implementing a simple machine learning model. Next, you'll create a cancer diagnosis classification pipeline, followed by tackling projects delving into stock price prediction, spam filtering, fraud detection, and a recommendation engine. The focus will be on application of ML techniques that classify data and make predictions, with an emphasis on automating data workflows with the Spark ML pipeline API. The book also showcases the best of Scala’s functional libraries and other constructs to help you roll out your own scalable data processing frameworks. By the end of this Scala book, you’ll have a firm foundation in Scala programming and have built some interesting real-world projects to add to your portfolio.
Table of Contents (9 chapters)
close

Overview of flight delay prediction


In this chapter, we will implement a logistic regression-based machine learning model to predict flight delays. This model learns from flight data described in the next section, Flight dataset at a glance

A real-life situation goes like this—travel company T has a new prediction feature in their booking system that is designed to enhance a customer's travel experience. How so? For example, say traveler X wants to get on Southwest flight SW1 from origin A (St Louis) to destination C (Denver) with a connection at city B (Chicago). If T's flight booking system could predict the odds of X's flight arriving late at Chicago, and furthermore the odds of missing the connecting flight as well, X has information at their disposal that lets him or her decide the next course of action. 

With these opening point made, let's take a look at our flight dataset. 

The flight dataset at a glance

Data analysis in this chapter relies on a flight dataset, a dataset consisting...

bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete