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Dima Kuchin
2018-03-07 15:36:51 +02:00
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@@ -108,6 +108,7 @@ A curated **and opinionated** list of resources for Chief Technology Officers, w
* [Awesome Machine Learning](https://github.com/josephmisiti/awesome-machine-learning) *(GitHub)* * [Awesome Machine Learning](https://github.com/josephmisiti/awesome-machine-learning) *(GitHub)*
* [Best resources of everyday ML learning](https://www.quora.com/As-a-data-scientist-what-is-your-best-resource-of-everyday-learning) *(Quora)* * [Best resources of everyday ML learning](https://www.quora.com/As-a-data-scientist-what-is-your-best-resource-of-everyday-learning) *(Quora)*
* [Machine Learning Crash Course: with TensorFlow APIs](https://developers.google.com/machine-learning/crash-course/) *(Google)* * [Machine Learning Crash Course: with TensorFlow APIs](https://developers.google.com/machine-learning/crash-course/) *(Google)*
* [Deep Learning For Coders](http://course.fast.ai)
* Big scale * Big scale
* [What is CAP Theorem?](https://www.quora.com/What-Is-CAP-Theorem-1) *(Quora)* * [What is CAP Theorem?](https://www.quora.com/What-Is-CAP-Theorem-1) *(Quora)*
* [CAP Theorem: Revisited](http://robertgreiner.com/2014/08/cap-theorem-revisited/) * [CAP Theorem: Revisited](http://robertgreiner.com/2014/08/cap-theorem-revisited/)