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Oreilly – Computational Thinking: Just Enough Math

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Oreilly - Computational Thinking: Just Enough Math

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

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  1. 这套视频是通过开源框架,包括图片、抽象代数、优化、贝叶斯统计以及更高级的内容如线性代数,为商务人士介绍“够用就好”的高等数学。这些内容被用于供应链优化、价格模型以及反诈骗,尤其是来自互联网的犯罪等。 在视频中 Paco Nathan会讨论:大数据;复杂问题的分解;模式识别;模式抽象等
    wilde(特殊组-翻译)2年前 (2014-09-14)