coursera-machine-learning 
This repository contains the weekly MATLAB assignments that I did in Machine Learning course in Coursera.
Comments/issues/PRs are welcomed!
Exercise 1 in Week 2
| Part Name |
Score |
Feedback |
| Warm-up Exercise |
10 / 10 |
Nice work! |
| Computing Cost (for One Variable) |
40 / 40 |
Nice work! |
| Gradient Descent (for One Variable) |
50 / 50 |
Nice work! |
| Feature Normalization |
0 / 0 |
Nice work! |
| Computing Cost (for Multiple Variables) |
0 / 0 |
Nice work! |
| Gradient Descent (for Multiple Variables) |
0 / 0 |
Nice work! |
| Normal Equations |
0 / 0 |
Nice work! |
|
100 / 100 |
|
Exercise 2 in Week 3
| Part Name |
Score |
Feedback |
| Sigmoid Function |
5 / 5 |
Nice work! |
| Logistic Regression Cost |
30 / 30 |
Nice work! |
| Logistic Regression Gradient |
30 / 30 |
Nice work! |
| Predict |
5 / 5 |
Nice work! |
| Regularized Logistic Regression Cost |
15 / 15 |
Nice work! |
| Regularized Logistic Regression Gradient |
15 / 15 |
Nice work! |
|
100 / 100 |
|
Exercise 3 in Week 4
| Part Name |
Score |
Feedback |
| Regularized Logistic Regression |
30 / 30 |
Nice work! |
| One-vs-All Classifier Training |
20 / 20 |
Nice work! |
| One-vs-All Classifier Prediction |
20 / 20 |
Nice work! |
| Neural Network Prediction Function |
30 / 30 |
Nice work! |
|
100 / 100 |
|
Exercise 4 in Week 5
| Part Name |
Score |
Feedback |
| Feedforward and Cost Function |
30 / 30 |
Nice work! |
| Regularized Cost Function |
15 / 15 |
Nice work! |
| Sigmoid Gradient |
5 / 5 |
Nice work! |
| Neural Network Gradient (Backpropagation) |
40 / 40 |
Nice work! |
| Regularized Gradient |
10 / 10 |
Nice work! |
|
100 / 100 |
|
Exercise 5 in Week 6
| Part Name |
Score |
Feedback |
| Regularized Linear Regression Cost Function |
25 / 25 |
Nice work! |
| Regularized Linear Regression Gradient |
25 / 25 |
Nice work! |
| Learning Curve |
20 / 20 |
Nice work! |
| Polynomial Feature Mapping |
10 / 10 |
Nice work! |
| Validation Curve |
20 / 20 |
Nice work! |
|
100 / 100 |
|
Exercise 6 in Week 7
| Part Name |
Score |
Feedback |
| Gaussian Kernel |
25 / 25 |
Nice work! |
| Parameters (C, sigma) for Dataset 3 |
25 / 25 |
Nice work! |
| Email Preprocessing |
25 / 25 |
Nice work! |
| Email Feature Extraction |
25 / 25 |
Nice work! |
|
100 / 100 |
|
Exercise 7 in Week 8
| Part Name |
Score |
Feedback |
| Find Closest Centroids (k-Means) |
30 / 30 |
Nice work! |
| Compute Centroid Means (k-Means) |
30 / 30 |
Nice work! |
| PCA |
20 / 20 |
Nice work! |
| Project Data (PCA) |
10 / 10 |
Nice work! |
| Recover Data (PCA) |
10 / 10 |
Nice work! |
|
100 / 100 |
|
Exercise 8 in Week 9
| Part Name |
Score |
Feedback |
| Estimate Gaussian Parameters |
15 / 15 |
Nice work! |
| Select Threshold |
15 / 15 |
Nice work! |
| Collaborative Filtering Cost |
20 / 20 |
Nice work! |
| Collaborative Filtering Gradient |
30 / 30 |
Nice work! |
| Regularized Cost |
10 / 10 |
Nice work! |
| Regularized Gradient |
10 / 10 |
Nice work! |
|
100 / 100 |
|
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