README.md

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