the final architecture of this article

The Japanese version is here:
(https://qiita.com/koyaaarr/items/259ad4f0d574497c5b08)

Introduction

Machine learning Proof of Concept (PoC) is very popular these days due to the recent AI boom. And afterward, if (very fortunately) you get good achievement in the PoC, you may want to put the PoC system into production. However, while a lot of knowledge has been shared about exploratory data analysis and building predictive models, there is still not much knowledge on how to put them into practice, especially in production.

In this article, we will examine what is needed technically during the transition from PoC to production operations. I hope that this…


This is how data is visualized using Jupyter Lab in the demo in this article

For those who want to get started with data analysis in Python

This article will introduce Jupyter Notebook and Jupyter Lab (collectively called Jupyter), very reliable tools for data analysis in Python.

Jupyter is already in common use in the data science world, but I would like to show its benefits with a demo.

Assumptions

In this article, I analyze data under the following conditions.

  • Analyze table data, not unstructured data such as images and texts
  • Analyze data of several GB or tens of thousands of records, rather than data of several TB or hundreds of millions of records
  • Do the exploratory analysis, rather than routine analysis

What is not written

The following items are not covered…

Ryo Koyajima / 小矢島 諒

Data Scientist at an EC company. Live in Japan.

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