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My R code for two projects that I did in my machine learning course at CSU East Bay

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###Machine Learning Course at CSU East Bay

These are the two projects that I did in the machine learning course I took in graduate school. Included are the project 1 instuctions and the csv files for both project 1 and 2 (1987.csv for project 1 and train.csv & test.csv for project 2). Project 2 was part of the "Titanic: Machine Learning from Disaster" Kaggle competition. Here is a link to the Kaggle page describing the problem.

Both of the projects are implemented in R, as the entire course was taught using R.

This course covered the following topics:

  • Feature Scaling
  • R Programming
  • K-NN
  • Naive Bayes and Text Classification
  • Decision Trees and Rules
  • Sparce Matrices
  • Linear Regression
  • Regression Trees and Model Trees
  • Model Evaluation
  • Artificial Neural Networks
  • Support Vector Machines (SVMs)
  • Regularization
  • Parallel Processing and Distributed Systems
  • Parameter Tuning
  • Boosting, Bagging, and Ensembles
  • Affinity Analysis and Association Rules
  • Clustering and K-Means
  • Cross-validation
  • MySQL and Relational Databases

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My R code for two projects that I did in my machine learning course at CSU East Bay

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