![]() ![]() ![]() Install with pyenvĪnother installation alternative is to use pyenv, a version management tool for Python. You can test that the installation succeeded by opening a new terminal and type python. Download Python 2 for MacOS.Īfter the download, install the software by following the installation guide. Go to the download link and select the MacOS version. Download and install Python 2Īt the moment I'm writing this, the latest version is 2.7.18. If you try to install Python 2 from Homebrew, it will not work because the package has been removed: Installation error of Python 2 using Homebrew.įortunately, you can get the latest version of Python 2 from the official download site. There are still many python scripts running on Python 2.7 that can't be upgraded for various reasons, so you might need to install it. Starting version 12.3 of Mac OS Monterrey, Python 2 was removed from macOS, and developers are encouraged to use Python 3 or other programming languages. It is supported by major operating systems, especially MacOS, where version 2 was installed with the operating system by default. Install Virtual Environments in Jupyter Notebook 04.Python is a programming language widely used for building software and web applications. ![]() Install the Python Environment for AI MacOS: 01. Install Virtual Environments in Jupyter Notebook 05. Install Ubuntu Desktop GUI (Bonus) Windows 10: 01. Install the Python Environment for AI 07. Install Virtual Environments in Jupyter Notebook 06. Install Windows Subsystem for Linux 2 02. Install the Python Environment for AI WSL2: 01. It also includes articles that contain instructions with explanations and screenshots to help readers learn about what’s happening. It includes articles that contain instructions with copy and paste code and screenshots to help readers get the outcome as soon as possible. This article is part of a mini-series that helps readers set up everything they need to start learning about artificial intelligence, machine learning, deep learning, and or data science. ![]()
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