Complat software training 101
  • Introduction
  • Day 1
  • Day 2
  • TODO
  • Linear regression
  • Tmux
  • quick link
  • CLI more - 1
  • Vim more - 1
  • MQ
  • iv - 1
  • iv - 2
  • iv - 3
  • clear Arch
  • lv - array
  • INTERVIEW - JS
  • RDKit - read/write
  • RDKit - process
  • RDKit - transform
  • RDKit - rxn
  • SYSTEM DESIGN - Question
  • SYSTEM DESIGN - EX1
  • SYSTEM DESIGN - EX2
  • SYSTEM DESIGN - EX3
  • SYSTEM DESIGN - EX99
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On this page
  • Outline
  • Installation & setting
  • Command line
  • Git
  • Python / Ipython Notebook
  • Homework

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Day 1

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Last updated 5 years ago

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Outline

  1. installation & setting

  2. command line

  3. git

  4. python

Installation & setting

git (

command line (zsh, oh-my-zsh)

python (

Command line

$ ls
$ ls -al

$ cd ..
$ cd DIRECTORY_PATH
$ pwd

$ mkdir DIR_NAME

$ touch FILE_NAME

$ mv OLD_NAME NEW_NAME

$ rm FILE_NAME
$ rm -rf FILE_FOLDER

Git

$ git init
$ git st
$ git diff
$ git commit -m "YOUR_TITLE"
$ git clone REPOSITORY_URL
$ git add .
$ git add FILE_NAME
$ git rebase -i COMMIT_NUMBER
$ git push 
$ git pull

EXERCISE: create your dotfile & push it to github

Python / Ipython Notebook

linear regression

camelCase
snake_case

Homework

  1. Practice command line, git, ipyhton notebook on your laptop.

  2. Study Numpy, Scipy, Matplotlib one more time.

Practice linear regression with another approach.

https://drive.google.com/open?id=0B4ioefrVlFNpSndaRHhtemdJc1k\
http://python-guide-pt-br.readthedocs.io/en/latest/dev/virtualenvs/
https://backlogtool.com/git-guide/tw/
https://www.programiz.com/python-programming#learn-python-tutorial
https://www.kaggle.com/jasonych99/python-data-visualizations
https://spin.atomicobject.com/2014/06/24/gradient-descent-linear-regression/
http://cs231n.github.io/python-numpy-tutorial/
https://www.datacamp.com/community/tutorials/python-numpy-tutorial#gs.=1WAXAo