Paco Nathan

Computational Thinking: Just Enough Math

Date: This event took place live on June 04 2014

Presented by: Paco Nathan

Duration: Approximately 60 minutes.

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Watch the webcast recording

The webcast introduces advanced math for business people — "just enough" to take advantage of open source frameworks — including graph theory, abstract algebra, optimization, bayesian statistics, and more advanced areas of linear algebra. These are needed for supply chain optimization, pricing models, and anti-fraud, especially given the increased data rates coming from the Internet of Things.

In the webcast, Paco Nathan will discuss how to:

  • Develop themes within the material to highlight a computational thinking approach for Big Data
  • Decompose a complex problem into smaller solvable problems
  • Leverage pattern recognition to identify when a known approach can be leveraged
  • Abstract from those patterns into generalizations as strategies
  • Articulate strategies as algorithms — general recipes for how to handle complex problems

He will also focus on morsels of advanced math, tying each new concept to a concrete business use case, showing brief code examples in Python.

This webcast previews Nathan's "Just Enough Math" tutorial at OSCON, based on the upcoming book by Paco and Allen Day.

About Paco Nathan

Paco Nathan, is known as a "player/coach"� data scientist who's led innovative Data teams building large-scale apps for 10+ years. As a recognized expert in distributed systems, machine learning, and Enterprise data workflows, Paco is an O'Reilly author "Enterprise Data Workflows with Cascading"� and an advisor for The Data Guild in Palo Alto, CA. Paco received his BS Math Sci and MS Comp Sci degrees from Stanford University, and has 25+ years technology industry experience ranging from Bell Labs to early-stage start-ups. Newsletter and "official" web site:

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