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My guess: using all amazon tools to get you tied into their stack. This is an Amazon MO I don't likeand have seen frequently (along withmany stockholm syndromed

My guess: using all amazon tools to get you tied into their stack. This is an Amazon MO I don't likeand have seen frequently (along withmany stockholm syndromed users). I hope I'm wrong though.

panpanna 6y ago
See for yourself https://github.com/aws-samples/aws-machine-learning-university-accelerated-nlp https://github.com/aws-samples/aws-machine-learning-universi... sklearn + mxnet ?
datameta 6y ago
I have seen the same for Microsoft and IBM. Too many virtual workshops during presentations, even with smaller companies, seek to teach the use of their simplified tool rather than instill under-the-hood knowledge or develop a skill in a broader scope.
giaour 6y ago
When I took some of these courses at Amazon, they were taught using open source tools like numpy and mxnet. Assignments and enrollments used an internal platform, and most hands-on work used a Jupyter-like platform that I don't believe is offered as an external service. There was a special session offered at one point that covered how to apply what you had learned using AWS services like SageMaker, but it wasn't integrated into the curriculum. (Not sure if this is still the case; I took MLU courses in early 2019.)
archgoon 6y ago
Amazon doesn't need to tell people to use their technology to benefit from educational videos. Completely ignoring the educational content itself, well made educational videos bring community good will. This helps in both purchasing decisions and recruitment. Honestly, this basically can come from a PR / recruiting budget. Lecturer's aren't that expensive. Now, for ML specifically, expanding the set of ML engineers has a dual benefit: 1) Creates more awareness and therefore demand for ML cloud services. Opensource? No problem, amazon will cheerfully sell you gpu enabled ec2 instances. 2) Expanded pool of candidates for hiring, and increased likelihood that internally, someone will propose a viable ML solution/product. The ML sector is still growing rapidly, anything that fuels its growth is going to benefit Amazon simply by virtue that they're always going to be in the running for any business purchasing decision, and probabilistically, they'll get a percentage cut of that growth. Education helps grow it, and educational videos are pretty dang cheap.

My guess: using all amazon tools to get you tied into their stack. This is an Amazon MO I don't likeand have seen frequently (along withmany stockholm syndromed users). I hope I'm wrong though.

panpanna 6y ago

See for yourself https://github.com/aws-samples/aws-machine-learning-university-accelerated-nlp https://github.com/aws-samples/aws-machine-learning-universi... sklearn + mxnet ?

datameta 6y ago

I have seen the same for Microsoft and IBM. Too many virtual workshops during presentations, even with smaller companies, seek to teach the use of their simplified tool rather than instill under-the-hood knowledge or develop a skill in a broader scope.

giaour 6y ago

When I took some of these courses at Amazon, they were taught using open source tools like numpy and mxnet. Assignments and enrollments used an internal platform, and most hands-on work used a Jupyter-like platform that I don't believe is offered as an external service. There was a special session offered at one point that covered how to apply what you had learned using AWS services like SageMaker, but it wasn't integrated into the curriculum. (Not sure if this is still the case; I took MLU courses in early 2019.)

archgoon 6y ago

Amazon doesn't need to tell people to use their technology to benefit from educational videos. Completely ignoring the educational content itself, well made educational videos bring community good will. This helps in both purchasing decisions and recruitment. Honestly, this basically can come from a PR / recruiting budget. Lecturer's aren't that expensive. Now, for ML specifically, expanding the set of ML engineers has a dual benefit: 1) Creates more awareness and therefore demand for ML cloud services. Opensource? No problem, amazon will cheerfully sell you gpu enabled ec2 instances. 2) Expanded pool of candidates for hiring, and increased likelihood that internally, someone will propose a viable ML solution/product. The ML sector is still growing rapidly, anything that fuels its growth is going to benefit Amazon simply by virtue that they're always going to be in the running for any business purchasing decision, and probabilistically, they'll get a percentage cut of that growth. Education helps grow it, and educational videos are pretty dang cheap.