This repository contains the weekly MATLAB assignments that I did in Machine Learning course in Coursera.
Comments/issues/PRs are welcomed!
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
