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Mastering Java for Data Science

You're reading from Mastering Java for Data Science

Product type Book

Published in Apr 2017

Publisher Packt

ISBN-13 9781782174271

Pages 364 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Alexey Grigorev

Table of Contents (17) Chapters

Title Page

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Data Science Using Java

2. Data Processing Toolbox

3. Exploratory Data Analysis

4. Supervised Learning - Classification and Regression

5. Unsupervised Learning - Clustering and Dimensionality Reduction

6. Working with Text - Natural Language Processing and Information Retrieval

7. Extreme Gradient Boosting

8. Deep Learning with DeepLearning4J

9. Scaling Data Science

10. Deploying Data Science Models

Case study - hardware performance

In this project, we will try to predict how much time it will take to multiply two matrices on different computers.

The dataset for this project originally comes from the paper Automatic selection of the fastest algorithm implementation by Sidnev and Gergel (2014), and it was made available at a machine learning competition organized by Mail.RU. You can check the details at http://mlbootcamp.ru/championship/7/.

Note

The content is in Russian, so if you do not speak it, it is better to use a browser with translation support.

You will find a copy of the dataset along with the code for this chapter.

This dataset has the following data:

m, k, and n represent the dimensionality of the matrices, with m*k being the dimensionality of matrix A and k*n being the dimensionality of matrix B
Hardware characteristics such as CPU speed, number of cores, whether hyper-threating is enabled or not, and the type of CPU
The operation system

The solution for this problem can be quite...

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Authors (1)

Alexey Grigorev

Alexey Grigorev is a skilled data scientist, machine learning engineer, and software developer with more than 8 years of professional experience. He started his career as a Java developer working at a number of large and small companies, but after a while he switched to data science. Right now, Alexey works as a data scientist at Simplaex, where, in his day-to-day job, he actively uses Java and Python for data cleaning, data analysis, and modeling. His areas of expertise are machine learning and text mining.

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