3_ Jupiter notebook, numpy and mattlotlib

The first 3 Chapter Jupyter Notebook, numpy and matplotlib

A good workman does his work well , You must sharpen your tools first . In this chapter , We will learn about the use of basic tools related to machine learning ：Jupyter Notebook, numpy and matplotlib.

3-1 Jupyter Notebook Basics

3-2 Jupyter Notebook The magic command in

After understanding the basic operations, you can hide some tool functions through the red box settings , To expand the area where the code is displayed .
Basic operation （ The coordinates of the mouse point in the code area ）

Reference documents
https://blog.csdn.net/enter89/article/details/90329754?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522162599154116780264079515%2522%252C%2522scm%2522%253A%252220140713.130102334…%2522%257D&request_id=162599154116780264079515&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2_allbaidu_landing_v2~default-1-90329754.first_rank_v2_pc_rank_v29&utm_term=jupyternotebook%E5%BF%AB%E6%8D%B7%E6%93%8D%E4%BD%9C

Shortcut key	paraphrase	function
A	after	Add a cell to the current cell
B	before	Add a cell under the current cell
L	line	Switch the description of the number of rows in the display cell
X		Cut the current cell , It can be used when deleting cells
–	–	–
Shift + Enter Run this unit , Select the next unit	–	Run this cell , Jump to the next cell
M	Markdown	The cell becomes a text description type
Y	yes, It's time for you to write code	Cells become code types

github There are related Markdown Syntax document for ：
https://guides.github.com/features/mastering-markdown/

3-3 Numpy Data base
3-4 establish Numpy Array ( And matrices )
3-5 Numpy Array ( And matrices ) Basic operation
3-6 Numpy Array ( And matrices ) The merger and division of
3-7 Numpy Matrix operations in
3-8 Numpy Aggregation operations in
3-9 Numpy Medium arg operation
3-10 Numpy The comparison between and Fancy Indexing
3-11 Matplotlib Fundamentals of data visualization
3-12 Data loading and simple data exploration