Anaconda distribution is the easiest way to perform Python data science and machine learning.
It includes more than 250 popular data science packages, as well as Conda packages and virtual environment managers for Windows,linux and MacOS.
Conda makes installing, running, and upgrading complex data science and machine learning environments (such as Scikit-learn,tensorflow and scipy) easier and faster. Anaconda Installation
Download Address:
https://www.anaconda.com/download/
At the top of the address, choose your own appropriate version,
After downloading, direct installation, Windows users can directly add to the environment variables on this hook, the rest of the next installation completed
After the installation is complete: View version confirmation that the installation was successful
Conda–version
There is a version of the output to indicate that the installation is in place
After the installation is complete, it is recommended to change the default workspace:
After Jupyter notebook is installed, the default workspace is the current user directory after startup. In order to facilitate the management of documents, it is often necessary to set up their own work space. Here's an easy way to set up your workspace.
Modify the Jupyter notebook shortcut. Right-click the Jupyter Notebook Shortcut-> property-> replace%USERPROFILE% in "target" with the directory you want, eg:f:\anacondaworkspace
Next double-click Jupyter Notebook run, you can witness the effect. Conda Introduction
PS:Conda is a Anaconda manager that can install, upgrade, and so on package package and environment environment, and Python's Pip is somewhat similar to Conda management of the Environment (virtual environment) Like virtualenv in Python.
To create a new environment:
Conda create–name [Environment name] python=3.5[specified version]
Next, activate
Activate [environment name]//windows
source activate [environment name]//linux or Mac
Exit environment
Deactivate [environment name]//windows
source deactivate [environment name]//linux or Mac
Delete environment
Conda remove–name [Environment name]–all Conda Management of packages (Package) similar to the PIP in Python
Install a Python package
Conda install [package name]
Conda Install NumPy
View installed Python packages
Conda List
Conda list-n [Environment name]//view Python package for specified environment
Delete Package
Conda remove-n [Environment name] [package name]
Conda remove-n [Environment name] NumPy