Book Image

The Data Science Workshop

By : Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, Dr. Samuel Asare
Book Image

The Data Science Workshop

By: Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, Dr. Samuel Asare

Overview of this book

You already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.
Table of Contents (18 chapters)

Correlation Matrix and Visualization

Correlation, as you know, is a measure that indicates how two variables fluctuate together. Any correlation value of 1, or near 1, indicates that those variables are highly correlated. Highly correlated variables can sometimes be damaging for the veracity of models and, in many circumstances, we make the decision to eliminate such variables or to combine them to form composite or interactive variables.

Let's look at how data correlation can be generated and then visualized in the following exercise.

Exercise 3.05: Finding the Correlation in Data to Generate a Correlation Plot Using Bank Data

In this exercise, we will be creating a correlation plot and analyzing the results of the bank dataset.

The following steps will help you to complete the exercise:

  1. Open a new Colab notebook, install the pandas packages and load the banking data:
    import pandas as pd
    file_url = '