Build a machine learning environment

Introduction

I wanted to build an environment for machine learning, but it seems that installing a special library that is used for machine learning as it is may cause the computer to start up strangely and the OS to start up. So, this time, I will introduce a method for building an OS-independent virtual environment to prevent such a situation. This time, we will introduce from the contents of Introduction to Machine Learning for Data Analysis.

Operating environment

The operating environment this time is

It is like this.

Building a virtual environment

First, use pip and enter the following command to install virtualenv.

$ sudo pip install --upgrade virtualenv

After installation, we will actually build a virtual environment with virtualenv. Enter the following command.

$ virtualenv --system-site-packages sample

This will create a directory called "sample". We will build a python execution environment here. If you no longer need it, you can easily uninstall it by deleting the entire directory. Let's take a look at how to specifically activate this virtual environment.

$ cd sample
＄ . ./bin/activate

After activating, the terminal display will change as follows.

(sample)$

The virtual environment is now running. To restore it, use the deactive command.

(sample)$ deactivate　

Installation of scikit-learn

Now install the machine learning library scikit-learn in this virtual environment. After activating the virtual environment you built earlier, enter the following command.

(sample)$ pip install -U scikit-learn

You have now installed scikit-learn. From now on, we will create a machine learning program using this scikit-learn.

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