Oreilly - Computational Thinking: Just Enough Math
Oreilly - Computational Thinking: Just Enough Math
English | .FLV | aac, 44100 Hz, stereo | h264, yuv420p, 1280x720, 29.97 fps(r) | 169MB
Genre: E-learning
English | .FLV | aac, 44100 Hz, stereo | h264, yuv420p, 1280x720, 29.97 fps(r) | 169MB
Genre: E-learning
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.
Screenshot:
Oreilly - Computational Thinking: Just Enough Math
