Packt+ | Advance your knowledge in tech

You're reading from Python: Advanced Guide to Artificial Intelligence Expert machine learning systems and intelligent agents using Python

Product type Course

Published in Dec 2018

Publisher Packt

ISBN-13 9781789957211

Length 764 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Authors (2):

Giuseppe Bonaccorso

Rajalingappaa Shanmugamani

View More author details

Table of Contents (31) Chapters

Title Page

About Packt

Contributors

Preface

1. Machine Learning Model Fundamentals FREE CHAPTER

2. Introduction to Semi-Supervised Learning

3. Graph-Based Semi-Supervised Learning

4. Bayesian Networks and Hidden Markov Models

5. EM Algorithm and Applications

6. Hebbian Learning and Self-Organizing Maps

7. Clustering Algorithms

8. Advanced Neural Models

9. Classical Machine Learning with TensorFlow

10. Neural Networks and MLP with TensorFlow and Keras

11. RNN with TensorFlow and Keras

12. CNN with TensorFlow and Keras

13. Autoencoder with TensorFlow and Keras

14. TensorFlow Models in Production with TF Serving

15. Deep Reinforcement Learning

16. Generative Adversarial Networks

17. Distributed Models with TensorFlow Clusters

18. Debugging TensorFlow Models

19. Tensor Processing Units

20. Getting Started

21. Image Classification

22. Image Retrieval

23. Object Detection

24. Semantic Segmentation

25. Similarity Learning

1. Other Books You May Enjoy

Leave a review - let other readers know what you think

Index

TensorFlow Serving on Kubernetes

According to https://kubernets.io:

Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.

TensorFlow models can be scaled to be served from hundreds or thousands of TF Serving services using Kubernetes clusters in the production environment. Kubernetes clusters can be run on all popular public clouds, such as GCP, AWS, Azure, as well as in your on-premises private cloud. So let us dive right in to learn to install Kubernetes and then deploy the MNIST model on Kubernetes Cluster.

Installing Kubernetes

We installed Kubernetes on Ubuntu 16.04 in a single-node local cluster mode as per the following steps:

Install LXD and Docker, which are prerequisites to install Kubernetes locally. LXD is the container manager that works with linux containers. We already learned how to install Docker in the previous section. To install LXD, run the following command:

$ sudo snap install lxd
lxd 2.19 from 'canonical'installed...

The rest of the chapter is locked

You're reading from Python: Advanced Guide to Artificial Intelligence Expert machine learning systems and intelligent agents using Python

Table of Contents (31) Chapters

TensorFlow Serving on Kubernetes

Installing Kubernetes

Unlock this book and the full library FREE for 7 days

Authors (2)

Personalised recommendations for you