Python、Markdown、HTML、LaTex、Javascipts、R、数据可视化等等

你会学到:
安装Python,设置windows新终端,安装Jupyter笔记本并创建Jupyter笔记本,创建工作目录并从终端访问
创建、显示和运行。py文件,运行外部IPython文件,用Markdown和HTML格式化文本,在Jupyter笔记本中运行R和Javascript
在Jupyter笔记本中创建、插入方程式、嵌入图像、音频和视频,并在Jupyter笔记本中对齐它们
改变主题,使用广泛使用的快捷方式,智能代码完成插件,多行光标,流行的魔法命令,直接在Jupyter notebo中安装软件包
在Jupyter笔记本中创建基本图、交互图和交互图小部件
为单个或多个笔记本创建内容表,并将笔记本转换为即时实时幻灯片和独立的web应用程序
解决了Windows上Jupyter笔记本内置终端不可用的问题,解决了Windows上R无法在一个驱动器上安装软件包的问题

MP4 |视频:h264,1280×720 |音频:AAC,44.1 KHz,2 Ch
语言:英语+中英文字幕(云桥网络 机译 |时长:28节课(7h 44m) |大小解压后:2.97 GB

要求
本课程不需要任何关于Python、Markdown、HTML和LaTex的知识,也不需要其他编程知识,尽管对它们有基本的了解将有利于更快地掌握技能。

描述
本课程由5个部分组成,包括27个章节,涵盖了Jupyter笔记本的核心,从基本概念、操作到详细应用。它包括

(1)安装Python,设置windows新终端,安装Jupyter笔记本并创建Jupyter笔记本,创建工作目录并从Windows终端访问;

(2)创建、显示和运行。py文件,运行外部IPython文件,在Jupyter笔记本中用Markdown和HTML格式化文本;

(3)创建表格,插入方程式,将图像、音频和视频嵌入Jupyter笔记本,并使用Markdown、HTML、Magics、IPython函数等进行对齐。

(4)改变主题,使用广泛使用的快捷方式、智能代码完成插件、多行光标、流行的魔法命令,直接在Jupyter笔记本中安装软件包,以及使用内置终端;

(5)在Jupyter笔记本中创建基础绘图、交互绘图和交互绘图小部件;

(6)为内部Jupyter笔记本和多个笔记本制作内容表,将笔记本转换为演示幻灯片,并将笔记本转移到web应用程序。

本课程使用实际的例子来帮助你从初学者到专家,以简单快捷的方式理解和掌握Jupyter笔记本。这一门课程足以让你掌握Jupyter笔记本的几乎所有方面

这门课是给谁的
程序员、业务分析师、数据分析师、统计学家和数据科学家,他们想学习如何使用Jupyter笔记本进行代码编写、数据分析和机器学习
它对正在学习和教授Python、数据分析和建模以及机器学习的学生和学术机构也很有帮助。
但是对于任何喜欢Python和Jupyter笔记本的人来说,这都是他/她的项目

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 28 lectures (7h 44m) | Size: 2.3 GB
Python, Markdown, HTML, LaTex, Javascipts, R, Data Visulization and many more

What you’ll learn:
Install Python, setup windows new terminal, install Jupyter notebook and create Jupyter notebook, create working directory and access it from the terminal
Create, display and run .py file, run external IPython files, formating text with Markdown and HTML, run R and Javascript in Jupyter notebook
Create, insert equations, embed images, audios and videos into Jupyter notebook and align them in Jupyter notebook
Change themes, use widely used shortcuts, smart code completion plugin, multi-line cursors, popular magic commands , install packages directly in Jupyter notebo
Create basic plots, interactive plots and interactive plot widget in Jupyter notebook
Create a content table for a single or multiple notebooks, and convert notebook to a instant and live slideshow and a standalone web application
Solve unavailable problem of Built-in terminal of Jupyter notebook on Windows, Solve problem of R unable to install packages on onedrive on Widows

Requirements
This course does not require any knowledge of Python, Markdown, HTML and LaTex, and other programming knowledge though a basic knowledge of them would be advantage to grasp the skills more quickly.

Description
This course consists of 5 Parts, including 27 lesson chapters, which cover the core of the Jupyter Notebook from the basic concepts, operations to detailed applications. It includes

(1) install Python, setup windows new terminal, install Jupyter notebook and create Jupyter notebook, create working directory and access it from Windows terminal;

(2) create, display and run .py file, run external IPython files, formating text with Markdown and HTML in Jupyter notebook;

(3) create tables, insert equations, embed images, audios and videos into Jupyter notebook and align them using Markdown, HTML, Magics, IPython functions, etc.

(4) change themes, use widely used shortcuts, smart code completion plugin, multi-line cursors, popular magic commands , install packages directly in Jupyter notebook, as well as use the built-in terminal;

(5) create basic plotting, interactive plotting and Interactive plot widget in Jupyter notebook;

(6) make a content table for an inside Jupyter notebook and for multiple notebooks , convert notebook to a presentation slideshow, and transfer a notebook to a web application.

This course uses practical examples to help you understand and grasp the Jupyter Notebook from a beginner to an expert in an easy and quick way. This one course is enough for you to grasp almost all aspect of the Jupyter notebook

Who this course is for
Programmers, business analysts, data analysts, statisticians, and data scientists, who want to learn how to use Jupyter notebook for code writing, data analysis and machine learning
It is also helpful to students and academic faculties, who are learning and teaching Python, data analysis and modelling, and machine learning.
But it can be for anyone who loves Python and Jupyter notebook for his/her projects

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