/Coursera_ML

Octave / Julia programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

Primary LanguageMATLAB

Coursera Machine Learning Assignments in Julia

author julia license contribution

title_image

About

This project aims to use Julia programming to complete the course assignments of Machine Learning on Coursera by Prof. Andrew Ng.

How to start

Dependencies

This project was coded in Julia 1.5

  • DelimitedFiles
  • Plots
  • LinearAlgebra
  • Statistics
  • Optim
  • LaTeXStrings

Installation

For example:

Pkg> add DelimitedFiles

Important Note

There are a couple of things to keep in mind before starting.

  • In Octave/Matlab, 
    >> [2 3] * [2; 3]
>> 13
    Now, it is 
    julia> [2 3] * [2; 3]
julia> [13]
    Therefore we recommended using dot function 
    julia> dot([2 3], [2; 3])
julia> 13

Contents

Exercise 1

  • Linear Regression
  • Linear Regression with multiple variables

Exercise 2

  • Logistic Regression
  • Logistic Regression with Regularization

Working...

Exercise 3

  • Multiclass Classification
  • Neural Networks Prediction fuction

Exercise 4

  • Neural Networks Learning

Exercise 5

  • Regularized Linear Regression
  • Bias vs. Variance

Exercise 6

  • Support Vector Machines
  • Spam email Classifier

Exercise 7

  • K-means Clustering
  • Principal Component Analysis

Exercise 8

  • Anomaly Detection
  • Recommender Systems