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00 Introduction.ipynb | 6 years ago | |
01 Basics.ipynb | 6 years ago | |
02 Print Statement.ipynb | 6 years ago | |
02 Print Statement.py | 6 years ago | |
03 Data Structure.ipynb | 6 years ago | |
03 Data Structure.py | 6 years ago | |
04 Data Structure 2.ipynb | 6 years ago | |
05 Control Flow.ipynb | 6 years ago | |
05 Control Flow.py | 6 years ago | |
06 Function.ipynb | 6 years ago | |
07 Class.ipynb | 6 years ago | |
07 Class.py | 6 years ago | |
Python.pdf | 6 years ago | |
README.md | 6 years ago |
Note: Andreas Ernst has improvised and updated the repo to python 3, Link
Python is a modern, robust, high level programming language. It is very easy to pick up even if you are completely new to programming.
Mac OS X and Linux comes pre installed with python. Windows users can download python from https://www.python.org/downloads/ .
To install IPython run,
$ pip install ipython[all]
This will install all the necessary dependencies for the notebook, qtconsole, tests etc.
Installing all the necessary libraries might prove troublesome. Anaconda and Canopy comes pre packaged with all the necessary python libraries and also IPython.
Download Anaconda from https://www.continuum.io/downloads
Anaconda is completely free and includes more than 300 python packages. Both python 2.7 and 3.4 options are available.
Download Canopy from https://store.enthought.com/downloads/#default
Canopy has a premium version which offers 300+ python packages. But the free version works just fine. Canopy as of now supports only 2.7 but it comes with its own text editor and IPython environment.
From the terminal
ipython notebook
In Canopy and Anaconda, Open the respective terminals and execute the above.
You can download the pdf copy from here : Get Started with Python
It is better to download all the ipython notebooks from this repository https://github.com/rajathkumarmp/Python-Lectures and learn it on the notebook itself rather than having to refer to a pdf.
Launch ipython notebook from the folder which contains the notebooks. Open each one of them
Cell > All Output > Clear
This will clear all the outputs and now you can understand each statement and learn interactively.
00 - Introduction and Installation
01 - Variable, Operators and Built-in Functions
02 - Print Statement, Precision and FieldWidth
These are online read-only versions.
This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/
机器学习越来越多应用到飞行器、机器人等领域,其目的是利用计算机实现类似人类的智能,从而实现装备的智能化与无人化。本课程旨在引导学生掌握机器学习的基本知识、典型方法与技术,通过具体的应用案例激发学生对该学科的兴趣,鼓励学生能够从人工智能的角度来分析、解决飞行器、机器人所面临的问题和挑战。本课程主要内容包括Python编程基础,机器学习模型,无监督学习、监督学习、深度学习基础知识与实现,并学习如何利用机器学习解决实际问题,从而全面提升自我的《综合能力》。
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