MachineLearningCourse.jl

A Julia package for machine learning course materials and implementations.

Installation

The recommended way to use this package is to load the module as follows:

using Pkg
Pkg.add(url="https://github.com/rajgoel/course-machine-learning", subdir="julia")

Usage

To use the module type:

using MachineLearningCourse

To run the demos type:

using MachineLearningCourse

# Run Lecture 01 simple prediction demo
Lecture01.demo()

# Run Lecture 02 gradient descent demo
Lecture02.demo()

# etc.

Lectures

• Lecture 01 - A simple linear classifier
• Lecture 02 - Vanilla implementation of gradient descent
• Lecture 03 - Vanilla and Flux.jl deep neural network implementation
• Lecture 04 - Stochastic gradient descent using Flux.jl
• Lecture 05 - Filtering, pooling, and convolution
• Lecture 06 - Graph convolutional networks (GCNs) for collaborative filtering
• Lecture 07 - Autoencoders
• Lecture 08 - Deep Q-Learning for the Breakout game
• Lecture 09 - Policy gradient methods for the Breakout game

Course material

using Pkg
Pkg.add(url="https://github.com/rajgoel/course-machine-learning", subdir="julia")

using MachineLearningCourse

# Run lecture demos
Lecture01.demo()
Lecture02.demo()
Lecture03.demo()
# etc.