Skip to content

Latest commit

 

History

History
75 lines (58 loc) · 3.04 KB

assignment0.md

File metadata and controls

75 lines (58 loc) · 3.04 KB
Raw


Syllabus | Slides and Assignments | Project | Lecturer

Python Basics

0. Learn Python basics on Codecademy (free version), w3schools, and the tutorial from the textbook

1. Install Python on your local machine.

  • Install conda with Python 3.8+.

2. Install required packages.

  • Open terminal.
conda install scikit-learn
conda install pandas

3. (Optional) Install an IDE.

Github Basics

0. Install Git and create your Github account.

  • Skip this step if you already have one.

1. Create a new PRIVATE repository called DSCI-633 under your Github account.

  • (1) Click on the new button:

  • (2) Initiate the new private repo:

  • (3) Invite the instructor and the TA as collaborators (GitHub ID: azhe825, manojb01):

2. Clone the DSCI-633 repo to your local machine.

git clone THE-COPIED-URL

3. Save username and token in git.

  • Create your personal access token on this page
  • Copy the generated token.
  • In terminal:
git config --global credential.helper manager
  • When running this command, the first time you pull or push from the remote repository, you'll get asked about the username and your token (NOT Password!). Afterwards, for consequent communications with the remote repository you don't have to provide the username and password.

4. Working with a github repo.

  • (1) Go to the local directory of the DSCI-633 repo.
  • (2) Pull from Github so that the content on your local machine is updated with the remote server of Github:
DSCI-633> git pull
  • (3) Work on your local machine (add/remove/edit files under DSCI-633/).
  • (4) Commit to the remote server of Github (upload local changes).
DSCI-633> git add .
DSCI-633> git commit -m "YOUR COMMIT MESSAGE"
DSCI-633> git push

5. Add your information to Google sheet

  • Add your github repo url (along with your RIT identifier and Github ID) to the Google sheet.
  • Make a self-evaluation on your current knowledge/expertise in coding, Python, and machine learning. This information will ONLY be used to decide your study group.