Skip to content

Update README.md #14

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Update README.md #14

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
# Coursera-Stanford-ML-Python
# Coursera-Stanford-ML-Python-AndrewNg

Coursera/Stanford Machine Learning course assignments in Python
Coursera/Stanford Machine Learning course assignments in Python :

[![Join the chat at https://gitter.im/sgang007/Coursera-Stanford-ML-Python](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/sgang007/Coursera-Stanford-ML-Python?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

Assignments for Andrew Ng's Machine Learning course implemented in Python without solutions in line with the [Coursera Code of Honor](https://www.coursera.org/about/terms/honorcode "Coursera Honor Code"). The code is structurally equivalent to the Matlab implementation from Coursera and the results are numerically equivalent with the correct Python implementation of the incomplete scripts. After completing each assignment, students can submit for grading to the Coursera website by executing the submit.py script. e.g below: (OSX or Linux) (On Windows change "export PYTHONPATH=../" to "set PYTHONPATH=..\")
Assignments for Andrew Ng's Machine Learning course implemented in Python without solutions in line with the [Coursera Code of Honor](https://www.coursera.org/about/terms/honorcode "Coursera Honor Code"). This code is structurally equivalent to the Matlab implementation from Coursera and the results are numerically equivalent with the correct Python implementation of the incomplete scripts. After completion of each assignment, students can submit for grading to the Coursera website by executing the submit.py script. e.g below: (OSX or Linux) (On Windows change "export PYTHONPATH=../" to "set PYTHONPATH=..\")

```
cd Coursera-Stanford-ML-Python/ex1
Expand Down