# Coursera Machine Learning Assigments

Assignments were completed with GNU Octave, version 3.8.0

# Course Schedule

## Week 1 (available March 3)

Introduction

Linear Regression with One Variable

(Optional) Linear Algebra Review

## Week 2 (available March 3)

Linear Regression with Multiple Variables

Octave Tutorial

Programming Exercise 1 (Linear regression)

## Week 3 (available March 24)

Logistic Regression

Regularization

Programming Exercise 2 (Logistic regression)

## Week 4 (available March 31)

Neural Networks: Representation

Programming Exercise 3 (Multi-class classification and neural networks)

## Week 5 (available April 7)

Neural Networks: Learning

Programming Exercise (Neural network learning)

## Week 6 (available April 14)

Advice for Applying Machine Learning

Machine Learning System Design

Programming Exercise (Bias-variance)

## Week 7 (available April 21)

Support Vector Machines (SVMs)

Programming Exercise (SVMs)

## Week 8 (available April 28)

Clustering

Dimensionality Reduction

Programming Exercise (K-Means and PCA)

## Week 9 (available May 5)

Anomaly Detection

Recommender Systems

Programming Exercise (Anomaly Detection and Recommender Systems)

## Week 10

Large-Scale Machine Learning

Example of an application of machine learning