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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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Section 4: Production and Deployment Challenges

The crucial feature of C++ is the ability of the program to be compiled and run on a variety of hardware platforms. You can train your complex machine learning model on the fastest GPU in the data center, and deploy it to tiny mobile devices with limited resources. This chapter will show you how to use the C++ APIs of the TensorFlow and Caffe2 libraries to build programs that use machine learning models for Android devices and in the cloud.

This section comprises the following chapters:

Chapter 12, Exporting and Importing Models
Chapter 13, Deploying Models on Mobile and Cloud Platforms

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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