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Hands-On Machine Learning with C++

You're reading from Hands-On Machine Learning with C++ Build, train, and deploy end-to-end machine learning and deep learning pipelines

Product type Paperback

Published in May 2020

Publisher Packt

ISBN-13 9781789955330

Length 530 pages

Edition 1st Edition

Languages

C++

Tools

Caffe

Concepts

Deep Learning

Author (1):

Kirill Kolodiazhnyi

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: Overview of Machine Learning

2. Introduction to Machine Learning with C++ FREE CHAPTER

3. Data Processing

4. Measuring Performance and Selecting Models

5. Section 2: Machine Learning Algorithms

6. Clustering

7. Anomaly Detection

8. Dimensionality Reduction

9. Classification

10. Recommender Systems

11. Ensemble Learning

12. Section 3: Advanced Examples

13. Neural Networks for Image Classification

14. Sentiment Analysis with Recurrent Neural Networks

15. Section 4: Production and Deployment Challenges

16. Exporting and Importing Models

17. Deploying Models on Mobile and Cloud Platforms

18. Other Books You May Enjoy

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Exploring linear methods for dimension reduction

This section describes the most popular linear methods that are used for dimension reduction.

Principal component analysis

Principal component analysis (PCA) is one of the most intuitively simple and frequently used methods for applying dimension reduction to data and projecting it onto an orthogonal subspace of features. In a very general form, it can be represented as the assumption that all our observations look like some ellipsoid in the subspace of our original space. Our new basis in this space coincides with the axes of this ellipsoid. This assumption allows us to get rid of strongly correlated features simultaneously since the basis vectors of the space we project them...

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Authors (1)

Kirill Kolodiazhnyi

Kirill Kolodiazhnyi

Kirill Kolodiazhnyi is a seasoned software engineer with expertise in custom software development. He has several years of experience building machine learning models and data products using C++. He holds a bachelor degree in Computer Science from the Kharkiv National University of Radio-Electronics. He currently works in Kharkiv, Ukraine where he lives with his wife and daughter.

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