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Data Science Algorithms in a Week

You're reading from Data Science Algorithms in a Week Top 7 algorithms for scientific computing, data analysis, and machine learning

Product type Paperback

Published in Oct 2018

Publisher Packt

ISBN-13 9781789806076

Length 214 pages

Edition 2nd Edition

Languages

Python

Tools

Devise

Concepts

Data Analysis

Authors (2):

David Toth

David Natingga

View More author details

Table of Contents (12) Chapters

Preface

1. Classification Using K-Nearest Neighbors

2. Naive Bayes FREE CHAPTER

3. Decision Trees

4. Random Forests

5. Clustering into K Clusters

6. Regression

7. Time Series Analysis

8. Python Reference

9. Statistics

10. Glossary of Algorithms and Methods in Data Science

11. Other Books You May Enjoy

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Electronics shop's sales – analyzing seasonality

We have data for sales in thousands of USD for a small electronics shop, by month, for the years 2010 to 2017. We would like to predict sales for each month of 2018:

Month/Year	2010	2011	2012	2013	2014	2015	2016	2017	2018
January	10.5	11.9	13.2	14.6	15.1	16.5	18.9	20
February	11.9	12.6	14.4	15.4	17.4	17.9	19.5	20.8
March	13.4	13.5	16.1	16.2	17.2	19.6	19.8	22.1
April	12.7	13.6	14.9	17.8	17.8	20.2	19.7	20.9
May	13.9	14.6	15.7	17.8	18.6	19.1	20.8	21.5
June	14	14.4	15.3	16.1	18.9	19.7	21.1	22.1
July	13.5	15.7	16.8	17.4	18.3	19.7	21	22.6
August	14.5	14	15.7	17	17.9	20.5	21	22.7
September	14.3	15.5	16.8	17.2	19.2	20.3	20.6	21.9
October	14.9	15.8	16.3	17.9	18.8	20.3	21.4	22.9
November	16.9	16.5	18.7	20.5	20.4	22.4	23.7	24
December	17.4	20.1	19.7	22.5	23	23.8	24.6	26.6

The data in the table is sales in thousands of USD

Analysis

To be able to analyze this, we will first graph the data so that we can observe patterns and analyze them:

From the graph and table, we notice that, in the long term, sales increase linearly. This is the trend. However, we can also see that the...

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Authors (2)

David Toth

David Toth

See other products by David Toth

Natingga

Natingga

Dvid Natingga graduated with a master's in engineering in 2014 from Imperial College London, specializing in artificial intelligence. In 2011, he worked at Infosys Labs in Bangalore, India, undertaking research into the optimization of machine learning algorithms. In 2012 and 2013, while at Palantir Technologies in USA, he developed algorithms for big data. In 2014, while working as a data scientist at Pact Coffee, London, he created an algorithm suggesting products based on the taste references of customers and the structures of the coffees. In order to use pure mathematics to advance the field of AI, he is a PhD candidate in Computability Theory at the University of Leeds, UK. In 2016, he spent 8 months at Japan's Advanced Institute of Science and Technology as a research visitor.

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