Abundant library, abundant information Execution environment construction is often troublesome Remarkably popular in the fields of machine learning and deep learning High-level general-purpose scripting language (executed line by line) Jupyter notebook is a famous editing environment for beginners who can execute and check code on a cell-by-cell basis. Explanation of how to build an environment to run Jupyter notebook Since the packages to be installed are managed on a directory basis, development can be done without polluting the execution environment of the PC itself. Explanation of how to build a directory-complete virtual environment using pipenv The reason for not using it will be described later. Do not use the famous Python environment installer Anaconda Explanation of building an environment where Python can be executed on a Windows machine using only VSCode (editor) and Python (interpreter) without using Anaconda. In addition to this article, there are many Web pages that explain similar content, so you may want to refer to that as well. I am not responsible for any problems that may occur with reference to this article, so please use this article as a reference only and take full responsibility for trying it out. In addition, the story of environment construction here will soon become old information, and there is a possibility that the method as written will not work in the future. Therefore, there are problems such as "unnecessarily itemized", "header structure is not good", "too many figures for Web document", etc., and it is far from "concise and easy-to-understand Qiita article". This article is a forcible drop of the laboratory materials originally created in PDF into Markdown.
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