Machine Learning with R

on YouTube ↗43m

" summary

The talk covers using R for machine learning and the performance limits R faces with large datasets, and presents the open-source H2O libraries as scalable, easy-to-use alternatives for executing ML algorithms on bigger data. It explains the main H2O libraries and how to integrate and use them from R.

AI-written summary · about

" chapters (12)

1. 0:00Introduction
2. 3:11Data world transition
3. 8:12Real-world data challenges
4. 13:09Hadoop and R issues
5. 20:14Need for accessible tools
6. 22:01What is H2O and its advantages
7. 25:14Installation and first steps
8. 27:47AutoML in H2O
9. 30:20Flow web interface
10. 32:44Real-time model deployment
11. 37:22Summary and limitations
12. 40:14Q&A

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