Basic knowledge of Anaconda

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