Machine Learning Algorithms

A collection of machine learning algorithms intended to enhance the knowledge of supervised, unsupervised, and reinforcement learning without the use of built in functions.

Table of Contents

• Unsupervised Learning
  

  • Association
    
    • Apriori
      
  • Clustering
    • K-means
      

• Supervised Learning
  

  • Classification
    
    • Logistic_Python
      
    • Logistic_R
      
    • K-Nearest Neighbor
      
    • Decision Tree
      
    • Random Forest
      
  • Regression
    • Simple Linear
      
    • Multiple Linear
      

• Reinforcment Learning
  

  • Deep Q
    

• _resources

  • Data
    
  • Images
    

Resources

Resources, include data and images, and can be found in the _resources folder. All images are public domain. Datasets were downloaded from Kaggle.com

Tech and Framework Used

• R
• Python
• Markdown
• Latex

How to use

Each algorithm contains two files; a .pdf and .Rmd/.ipynb. You can view the content by clicking on the PDF. You can also download main.Rmd and open it in Rstudio to view and alter the source code.