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Julia for Data Science

You're reading from Julia for Data Science high-performance computing simplified

Product type Paperback

Published in Sep 2016

Publisher Packt

ISBN-13 9781785289699

Length 346 pages

Edition 1st Edition

Languages

Julia

Concepts

Data Science

Author (1):

Anshul Joshi

View More author details

Table of Contents (12) Chapters

Preface

1. The Groundwork – Julia's Environment

2. Data Munging FREE CHAPTER

3. Data Exploration

4. Deep Dive into Inferential Statistics

5. Making Sense of Data Using Visualization

6. Supervised Machine Learning

7. Unsupervised Machine Learning

8. Creating Ensemble Models

9. Time Series

10. Collaborative Filtering and Recommendation System

11. Introduction to Deep Learning

Unicode plots

Unicode plots are really useful when we want to plot on the REPL. They are extremely lightweight.

Installation

There are no dependencies, so they can be installed easily:

Pkg.add("UnicodePlots") 
using UnicodePlots

Examples

Let's walk through the basic plots that can be made easily using UnicodePlots.

Generating Unicode scatterplots

Scatterplots are used to determine the correlation between two variables, that is, how one is affected by the other:

Generating Unicode line plots

A line plot displays the dataset in a series of data points:

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Authors (1)

Anshul Joshi

Anshul Joshi

Anshul Joshi is a data scientist with experience in recommendation systems, predictive modeling, neural networks, and high performance computing. His research interests encompass deep learning, artificial intelligence, and computational physics. Most of the time, he can be caught exploring GitHub or trying anything new he can get his hands on. You can also follow his personal blog.

See other products by Anshul Joshi

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