3 ms·
There is a website for the lessons too: https://madewithml.com/ https://madewithml.com/ Disclosure: I'm a contributor in their open-source community activities
by lineardigress 5y ago
There is a website for the lessons too: https://madewithml.com/ https://madewithml.com/
Disclosure: I'm a contributor in their open-source community activities and also in the ML space. Feel open to reach out to me if you have any questions.
- roflchoppa 5y agoThat’s one way to self promote. Cool repo.
- wunderwuzzi23 5y agoGood stuff, at high level it seems security engineering aspects might be missing. I put together content around threat modeling, infrastructure attacks as well as ML specific attacks with practical examples (like using adversarial robustness toolbox from Linux foundation). Details here: https://github.com/wunderwuzzi23/mlattacks https://github.com/wunderwuzzi23/mlattacks
- raghavbali 5y agoSomething I have been looking for quite some time. Thank you for this.
- lineardigress 5y agoPersonally there are many ways to implement machine learning in production and this resource does a good job on giving you a detailed grand tour of all the fundamentals you need to think about. And to make the concepts more concrete, each unit has code implementation for an end-to-end project. While some lessons can stand to be more well connected to the end-to-end project, the sheer amount of detail on some of the lessons simply don't exist anywhere else. The testing (https://madewithml.com/courses/mlops/testing/ https://madewithml.com/courses/mlops/testing/) and monitoring (https://madewithml.com/courses/mlops/monitoring/ https://madewithml.com/courses/mlops/monitoring/) lessons are clear examples of this.