From 9674fc97c697ee3972bd62227600d809c5ea118a Mon Sep 17 00:00:00 2001 From: Marcel Stampfer Date: Wed, 28 Oct 2015 20:16:25 +0000 Subject: [PATCH 1/6] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 383cadd..cd7e3af 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # Coursera-Stanford-ML-Python Coursera/Stanford Machine Learning course assignments in python -Assignments for Andrew Ng's Machine Learning course implemented in python. The code and results are structurally and numerically equivalent to the Matlab implementation from Coursera. Students can submit the assignments to the Coursera website by executing the submit.py script. The credentials will be saved to a file for subsequent submissions, e.g: +Assignments for Andrew Ng's Machine Learning course implemented in python without solutions and is thus 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 can be numerically equivalent with the correct python implementation of the incomplete scripts. After completing each assignment, students can submit to the Coursera website for grading by executing the submit.py script. The credentials will be saved to a file for subsequent submissions, e.g: ```bash cd Coursera-Stanford-ML-Python/ex1 @@ -22,4 +22,4 @@ Password: == -------------------------------- == | 10 / 100 | ``` -# Copy + From 9d6364d3fca3563f7ad105d8ccc339f8e17057f5 Mon Sep 17 00:00:00 2001 From: Marcel Stampfer Date: Wed, 28 Oct 2015 20:17:09 +0000 Subject: [PATCH 2/6] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index cd7e3af..8a2df5d 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # Coursera-Stanford-ML-Python Coursera/Stanford Machine Learning course assignments in python -Assignments for Andrew Ng's Machine Learning course implemented in python without solutions and is thus 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 can be numerically equivalent with the correct python implementation of the incomplete scripts. After completing each assignment, students can submit to the Coursera website for grading by executing the submit.py script. The credentials will be saved to a file for subsequent submissions, e.g: +Assignments for Andrew Ng's Machine Learning course implemented in python without solutions and is thus 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 can be numerically equivalent with the correct python implementation of the incomplete scripts. After completing each assignment, students can submit to the Coursera website for grading by executing the submit.py script. The credentials will be saved to a file for subsequent submissions, e.g: ```bash cd Coursera-Stanford-ML-Python/ex1 From ade4e2b2191193bfa1b8d0f1663be380aef7de9f Mon Sep 17 00:00:00 2001 From: Marcel Stampfer Date: Wed, 28 Oct 2015 20:18:11 +0000 Subject: [PATCH 3/6] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8a2df5d..34c7b65 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # Coursera-Stanford-ML-Python Coursera/Stanford Machine Learning course assignments in python -Assignments for Andrew Ng's Machine Learning course implemented in python without solutions and is thus 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 can be numerically equivalent with the correct python implementation of the incomplete scripts. After completing each assignment, students can submit to the Coursera website for grading by executing the submit.py script. The credentials will be saved to a file for subsequent submissions, e.g: +Assignments for Andrew Ng's Machine Learning course implemented in python without solutions and is thus 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 can be numerically equivalent with the correct python implementation of the incomplete scripts. After completing each assignment, students can submit to the Coursera website for grading by executing the submit.py script. The login credentials will be saved to a file for subsequent submissions, e.g: ```bash cd Coursera-Stanford-ML-Python/ex1 From 9caca0e92f181571c276fbfb4a477a973d4c2b52 Mon Sep 17 00:00:00 2001 From: Marcel Stampfer Date: Thu, 29 Oct 2015 00:10:51 +0000 Subject: [PATCH 4/6] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 34c7b65..c00296d 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # Coursera-Stanford-ML-Python Coursera/Stanford Machine Learning course assignments in python -Assignments for Andrew Ng's Machine Learning course implemented in python without solutions and is thus 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 can be numerically equivalent with the correct python implementation of the incomplete scripts. After completing each assignment, students can submit to the Coursera website for grading by executing the submit.py script. The login credentials will be saved to a file for subsequent submissions, e.g: +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 to the Coursera website for grading by executing the submit.py script. The login credentials will be saved to a file for subsequent submissions, e.g: ```bash cd Coursera-Stanford-ML-Python/ex1 From b9deee0a14a867ba09883fd4241a7c36e9f43137 Mon Sep 17 00:00:00 2001 From: Marcel Stampfer Date: Thu, 29 Oct 2015 14:04:31 +0000 Subject: [PATCH 5/6] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index c00296d..ffde06b 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,11 @@ # Coursera-Stanford-ML-Python Coursera/Stanford Machine Learning course assignments in python -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 to the Coursera website for grading by executing the submit.py script. The login credentials will be saved to a file for subsequent submissions, e.g: +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 to the Coursera website for grading by executing the submit.py script. The login credentials will be saved to a file for subsequent submissions, e.g on OSX or Linux (on Windows change "export PYTHONPATH=../" to "set PYTHONPATH=..\"): ```bash cd Coursera-Stanford-ML-Python/ex1 +export PYTHONPATH=../ python submit.py login (Email address): From 6a794a86e5711c4239486621082d36946bb60af9 Mon Sep 17 00:00:00 2001 From: Marcel Stampfer Date: Thu, 29 Oct 2015 16:24:30 +0000 Subject: [PATCH 6/6] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index ffde06b..34b6d4d 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # Coursera-Stanford-ML-Python Coursera/Stanford Machine Learning course assignments in python -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 to the Coursera website for grading by executing the submit.py script. The login credentials will be saved to a file for subsequent submissions, e.g on 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"). 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=..\") ```bash cd Coursera-Stanford-ML-Python/ex1 @@ -24,3 +24,4 @@ Password: == | 10 / 100 | ``` +The login credentials will be saved to a file for subsequent submissions,