Dan's Machine Learning Class

This is a self paced class with 3 separate technology tracks:

1. The Dan-Track:

• http://madlib.net (http://madlib.net/)

• http://scikit-learn.org (http://madlib.net/)

• http://www.csie.ntu.edu.tw/~cjlin/libsvm/

2. The R-Track: ML software from CRAN

3. The MATLAB track

Possible future tracks:

-SPARK

-Impala

-0xdata-H2O

-Oracle Data Mining ML API

You can start at any time.

You work independently, but with access to the instructor and other students.

Interaction is both face to face and online.

This class approaches Machine Learning (ML) as software with an API.

Most ML classes focus on under-the-hood topics like Gradient Descent.

This class presents ML more as a 'black box'.

This class helps you connect your ML project to a variety of APIs available from the technology tracks.

The data we feed to our ML projects will come from Yahoo finance as stock prices.

Stock price data is constantly changing, diverse, and interesting.

It makes excellent learning material.

The first class will deal with getting your learning environment setup.

I have great success with running my ML projects on Linux hosts.

You can run Linux hosts inside your laptop using virtualization software.

Also you can run them remotely in large data centers for pennies per hour.

I may be able to get you some free compute time from local cloud providers.

The aim of this class is to get you proficient at building a simple system which pulls in prices once a day, issues predictions, and then helps you visualize the accuracy of your project.

Once you are finished with that, you will be ready for a wide variety of ML projects.

The forum is here:

https://groups.google.com/forum/#!forum/bikletech

The Homework is here:

http://www.spy611.com/blog/class

e-me if you have questions: dan.bikle@gmail.com