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Linear Regression, Logistic Regression, Sentiment Analysis, Decision trees, clustering, visualization. Created by: Justin Nuñez

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Machine Learning with R!

In God we trust, all other brings data. - William Deming


How to read a data set into R. The web-link to your .csv file goes inside quotations.

IBM = read.csv(" ")

For python you could just do

import pandas as pd
IBM = pd.read_csv(" ")

If you don't have a link to the data, and it is saved on your computer in .csv format here is a website that shows you how to access it in R. The same will go for python. However, use the function

pd.read_csv()

I will analyze data from different data sets.

  • This repo will show you how to plot, manipulate, and analyze data. And hopefully give you enough skills to go further.

This is a nice website for basic R commands for data analysis.

What you will find:

  1. Analyzing .csv files
  2. Linear Regression
  3. Logistic Regression
  4. Text Analytics (Sentiment Analysis using Twitter)
  5. Hierarchical Clustering
  6. Random Forest
  7. CART models
much more to come

Want to learn machine learning?

  1. I recommend Andrew Ng's Machine learning course. You could also find an updated version on coursera.
  2. I recommend reading Introduction to Statisical learning with Applications in R.
  • Really Awesome Book!
  1. To be implemented with number 2 for way way way more (beneficial) theory is Elements of Statistical Learning.
  2. Had to add this book on R. It is too good. Too good.

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Linear Regression, Logistic Regression, Sentiment Analysis, Decision trees, clustering, visualization. Created by: Justin Nuñez

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