I presented at the
Cleveland SciPy/Julia/R Data Science Group on 6/14. The talk is a fairly high-level introduction to some of the machine learning methods and packages available in R.
Here is the video:
Here are the
Here are the
I presented at the Cleveland R User Group on using
xgboost in R.
Slides are available
Code (jupyter notebooks) are
Feedback welcome. Enjoy!
TensorFlow as open source for community use and improvement. From the site: “TensorFlow™ is an open source software library for numerical computation using data flow graphs.”
instructions on tensorflow.org are aimed at Ubuntu and OS X. I had a need to install it on CentOS so I documented the steps in a github gist. Feel free to comment if you find something I missed:
* Updated 8/18/2016 for TensorFlow 0.10
* Updated gist 10/18/2016 to correct typo in epel-release
January meeting, I presented on Linear Algebra basics in R. I have been taking the Andrew Ng’s Stanford Machine Learning course. That course primarily uses Matlab (or Octave, and open source equivalent), and machine learning involves manipulating and calculating with matrices. Naturally, being an R person, I have been working with some of the techniques in R.
In order to limit the scope of the talk, I focused on matrices, vectors and basic operations with them. There is a practical example that uses a machine learning algorithm, but it’s just to show how R handles a more involved equation with matrices. The talk is not an attempt to teach machine learning.
slides are available here, and comments or suggestions are welcome.
I have been buffing up on some areas of Math that I felt rusty in. One of the tools I was using was my
old TI-82 calculator I used in high school.
I even got the TI Connect software working where I could download screenshots, etc.
You can put in data sets (see screen cap below), and do some graphing and some statistical analysis.
However, mapping functions is a more straight forward use of the calculator. Which got me thinking… How does one do that in R?
I did a little digging. With the traditional R graphics and plotting functions, you would use curve() to draw a function. It works fine, but I like to use
ggplot2 when I can.
Turns out ggplot2 supports this well. The following code sample maps the same functions I was mapping on the calculator (sin, cos, and tan from 0 to 2pi radians).
And the resulting graph is…