A companion wiki + code repository for the O'Reilly Media video "Just Enough Math". This site provides additional links, sample code, and other addenda.
Python R
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
dat
src main web site link Jul 11, 2014
.gitignore
LICENSE fixed CC license Jul 11, 2014
README.md

README.md

Just Enough Math

This is a companion wiki + code repository for the O'Reilly Media video Just Enough Math which provides additional links, sample code, and other addenda.


With the commercial successes of machine learning and cloud computing, many business people need just enough math to take advantage of open source frameworks for big data. This course from Paco Nathan and Allen Day presents useful areas of advanced math in easy-to-digest morsels. If you’re familiar with high school Algebra 2 and basic statistics, you’re good to go.

You’ll learn newly introduced math concepts through business use cases, brief Python code examples, and lots of figures and illustrations. By the end of the course, you’ll understand how a variety of advanced math techniques get leveraged: complex graphs, sparse matrices, Bayesian priors, optimization solvers, etc.

  • Learn advanced math through simple equations and illustrations
  • Get tangible examples such as Lego blocks for data workflows
  • Explore the math examples through typical business use cases
  • Understand how these concepts tie into common business frameworks
  • Follow a case study of the Foobartendr.io company throughout the course

Computational Thinking

Throughout this material, we use an instructional rubric called computational thinking to develop themes for how to approach for Big Data. Some great resources for CT include:

Programming Environment

Most all of the programming examples are based on small sections of Python code. If you have Python installed, then launch its command line prompt and proceed to cut and paste the example code.

To get Python installed on your laptop, we recommend using the free download of Anaconda from Continuum Analytics.

We have prepared a GitHub gist to provide the input data and expected results for many of the code examples:

We recommend two excellent resources for learning to program in Python:

Some external sites that also get referenced in the examples include:


Other Resources

Part of the intended purpose for this video+book+tutorial series of material is to provide many links to other resources. The interested reader has plenty of "jumping" points from which to explore particular topics in depth: