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Machine learning reorg

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Dima Kuchin
2022-12-21 16:48:58 +02:00
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parent 61940c2927
commit 33830b788f
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@@ -186,12 +186,6 @@ A curated and **opinionated** list of resources for [Chief Technology Officers a
* Javascript * Javascript
* [JS: The Right Way](http://jstherightway.org) * [JS: The Right Way](http://jstherightway.org)
* [Frontend developer handbook 2019](https://frontendmasters.com/guides/front-end-handbook/2019/) * [Frontend developer handbook 2019](https://frontendmasters.com/guides/front-end-handbook/2019/)
* Machine Learning
* [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)*
* [Machine Learning Crash Course: with TensorFlow APIs](https://developers.google.com/machine-learning/crash-course/) *(Google)*
* [Deep Learning For Coders](https://course.fast.ai)
* [Weapons of Math Destruction](https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction)
* 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](https://robertgreiner.com/cap-theorem-revisited/) * [CAP Theorem: Revisited](https://robertgreiner.com/cap-theorem-revisited/)
@@ -218,6 +212,12 @@ A curated and **opinionated** list of resources for [Chief Technology Officers a
* [Building a data science team](https://fastdatascience.com/building-a-data-science-team/) * [Building a data science team](https://fastdatascience.com/building-a-data-science-team/)
* [Managing Data Science Teams](https://www.dominodatalab.com/resources/field-guide/managing-data-science-teams/) * [Managing Data Science Teams](https://www.dominodatalab.com/resources/field-guide/managing-data-science-teams/)
* [How to Structure a Data Science Team](https://www.altexsoft.com/blog/datascience/how-to-structure-data-science-team-key-models-and-roles/) * [How to Structure a Data Science Team](https://www.altexsoft.com/blog/datascience/how-to-structure-data-science-team-key-models-and-roles/)
* Machine Learning
* [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)*
* [Machine Learning Crash Course: with TensorFlow APIs](https://developers.google.com/machine-learning/crash-course/) *(Google)*
* [Deep Learning For Coders](https://course.fast.ai)
* [Weapons of Math Destruction](https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction)
## Startups ## Startups