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+# 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:
+
+```bash
+cd Coursera-Stanford-ML-Python/ex1
+python submit.py
+
+login (Email address): 
+Password: 
+==
+==                                   Part Name |     Score | Feedback
+==                                   --------- |     ----- | --------
+==                            Warm up exercise |  10 /  10 | Nice work!
+==           Computing Cost (for one variable) |   0 /  40 | 
+==         Gradient Descent (for one variable) |   0 /  50 | 
+==                       Feature Normalization |   0 /   0 | 
+==     Computing Cost (for multiple variables) |   0 /   0 | 
+==   Gradient Descent (for multiple variables) |   0 /   0 | 
+==                            Normal Equations |   0 /   0 | 
+==                                   --------------------------------
+==                                             |  10 / 100 |
+```
+# Copy