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How to configure Environment in Python Machine Learning

2025-01-16 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Development >

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Editor to share with you how to configure the environment in Python machine learning, I believe most people do not know much about it, so share this article for your reference, I hope you can learn a lot after reading this article, let's learn about it!

Anaconda installation

Official link to anaconda: Anaconda | The World's Most Popular Data Science Platform

Click Get Started

Click Download Anaconda installers

Download the corresponding installation package according to your operating system.

Install anaconda

Click all the way down and the installation is complete.

Configure the python3.6 environment using conda

At present, the stable version of python3 is 3.6. a virtual environment of python3 is built through anaconda.

First, let's take a look at the python version of the base environment. Click on the search bar of windows, type anaconda, and open Anaconda Prompt.

Enter a command

Conda create-n pytorch python=3.6

Build a virtual environment called pytorch. And activate the environment, enter the command.

Configuration and use of Spyder

Pycharm as a whole, the best IDE,Spyder for python is the IDE provided by Anaconda, which I think is easier to use when editing some simple programs or debugging programs. Here's a recommendation.

Open Anaconda Navigator.

Upgrade and switch the pytorch environment we just activated.

Open Spyder

You can select part of the code, press F9, and execute only the selected code block, which is suitable for debugging.

Install PyTorch

Log on to the PyTorch website: PyTorch

Select the operating system, cuda mode, copy the installation command.

Anaconda Prompt activates the pytorch environment and executes the command. Wait for the installation.

If you find that the installation is slow, it is recommended to add a domestic source to anaconda. And I don't recommend Tsinghua Yuan, because it's too stuck. Here I would like to recommend the source of Beiwai. The specific operations are as follows:

Open the .condarc file in the user directory and update it as follows.

Channels:

-defaults

Show_channel_urls: true

Default_channels:

-https://mirrors.bfsu.edu.cn/anaconda/pkgs/main

-https://mirrors.bfsu.edu.cn/anaconda/pkgs/r

-https://mirrors.bfsu.edu.cn/anaconda/pkgs/msys2

Custom_channels:

Conda-forge: https://mirrors.bfsu.edu.cn/anaconda/cloud

Msys2: https://mirrors.bfsu.edu.cn/anaconda/cloud

Bioconda: https://mirrors.bfsu.edu.cn/anaconda/cloud

Menpo: https://mirrors.bfsu.edu.cn/anaconda/cloud

Pytorch: https://mirrors.bfsu.edu.cn/anaconda/cloud

Simpleitk: https://mirrors.bfsu.edu.cn/anaconda/cloud

Execute the command on the command line to clean up the cache.

Conda clean-I

After the installation is complete, check the pytorch version.

Conda list

These are all the contents of the article "how to configure the Environment in Python Machine Learning". Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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