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Data Analysis with Python

You're reading from   Data Analysis with Python A Modern Approach

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789950069
Length 490 pages
Edition 1st Edition
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Author (1):
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David Taieb David Taieb
Author Profile Icon David Taieb
David Taieb
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Table of Contents (14) Chapters Close

Preface 1. Programming and Data Science – A New Toolset FREE CHAPTER 2. Python and Jupyter Notebooks to Power your Data Analysis 3. Accelerate your Data Analysis with Python Libraries 4. Publish your Data Analysis to the Web - the PixieApp Tool 5. Python and PixieDust Best Practices and Advanced Concepts 6. Analytics Study: AI and Image Recognition with TensorFlow 7. Analytics Study: NLP and Big Data with Twitter Sentiment Analysis 8. Analytics Study: Prediction - Financial Time Series Analysis and Forecasting 9. Analytics Study: Graph Algorithms - US Domestic Flight Data Analysis 10. The Future of Data Analysis and Where to Develop your Skills A. PixieApp Quick-Reference Other Books You May Enjoy Index

Overview of Kubernetes

Kubernetes (https://kubernetes.io) is a scalable open source system for automating and orchestrating the deployment and management of containerized applications, which are very popular among cloud service providers. It is most often used with Docker containers (https://www.docker.com) although other types of containers are supported. Before you start, you will need access to a set of computers that have been configured as a Kubernetes cluster; you can find a tutorial on how to create such a cluster here: https://kubernetes.io/docs/tutorials/kubernetes-basics.

If you don't have the computer resources, a good solution would be to use a public cloud vendor that provides a Kubernetes service, such as Amazon AWS EKS (https://aws.amazon.com/eks), Microsoft Azure (https://azure.microsoft.com/en-us/services/container-service/kubernetes), or IBM Cloud Kubernetes Service (https://www.ibm.com/cloud/container-service).

To better understand how a Kubernetes...

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