My name is John Horn and I am passionate about using data to better the world. My professional interests include Machine Learning, Data Mining, Automation, Spatial Modeling, Interactive Data Visualization, and Statistical Models.

Below are classes I have completed as well as books that have been very influential. In **Bold** are the resources I would highly recommend.

Classes

**’15 Johns Hopkins Data Science Coursera, Exploratory Data Analysis**

’14 Johns Hopkins Data Science Coursera, Getting and Cleaning Data

**’14 Johns Hopkins Data Science Coursera, R Programming**

’14 Johns Hopkins Data Science Coursera, The Data Scientist’s Toolbox

**’14 Intro to Hadoop and MapReduce, Cloudera / Udacity
**’12 UCI, Geoscience Modeling and Data Analysis ESS 212

’11 Stanford, Fundamentals of Modeling EESS 211

’11 Stanford, Fundamentals of Modeling EESS 211

**’11 Stanford, Advanced Statistical Methods for Earth System Analysis EESS 260**

’11 Stanford, Introduction to Probability and Statistics for Engineers CME 106

Books

**Introductory Time Series with R, Cowpertwait and Metcalfe, 978-0-387-88697-8
Applied Predictive Modeling, Kuhn and Johnson, ISBN-13: 978-1461468486**

**Python for Data Analysis, Wes Mckinney, 978-1782161417**

**Programming Collective Intelligence: Building Smart Web 2.0 Applications**

The Art of R Programming, Matloff,

*ISBN*-13: 858-2592222227

The Linux Command Line, Shotts, ISBN-13: 978-1593273897

**Learning Python, Lutz, ISBN-13: 978-1449355739**

Building Machine Learning Systems with Python, Willi Richert, 1782161406