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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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Technical requirements

The technologies you'll need for this chapter are as follows:

The Shogun-toolbox library
The Shark-ML library
The Dlib library
The plotcpp library
A modern C++ compiler with C++17 support
The CMake build system, version >= 3.8

The code files for this chapter can be found at the following GitHub repo: https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-CPP/tree/master/Chapter06

The rest of the chapter is locked

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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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