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Stefano Bosisio is an accomplished MLOps Engineer with a solid background in Biomedical Engineering, focusing on cellular biology, genetics, and molecular simulations.
[29:43] Key components of ML pipelines are essentia
l[33:47] Create a generalizable AI training pipeline with Kubeflow
[35:44] Consider cost-effective algorithms and deployment methods
[39:02] Agree with dream platform; LLMs require simple microservice
[42:48] Auto scaling: crucial, tricky, prone to issues
[46:28] Auto-scaling issues with Apache Beam data pipelines
[49:49] Guiding students through MLOps with practical experience
[53:16] Bulletproof Problem Solving: Decision trees for problem analysis
[55:03] Evaluate tools critically; appreciate educational opportunities
[57:01] Wrap up
4.9
2020 ratings
Stefano Bosisio is an accomplished MLOps Engineer with a solid background in Biomedical Engineering, focusing on cellular biology, genetics, and molecular simulations.
[29:43] Key components of ML pipelines are essentia
l[33:47] Create a generalizable AI training pipeline with Kubeflow
[35:44] Consider cost-effective algorithms and deployment methods
[39:02] Agree with dream platform; LLMs require simple microservice
[42:48] Auto scaling: crucial, tricky, prone to issues
[46:28] Auto-scaling issues with Apache Beam data pipelines
[49:49] Guiding students through MLOps with practical experience
[53:16] Bulletproof Problem Solving: Decision trees for problem analysis
[55:03] Evaluate tools critically; appreciate educational opportunities
[57:01] Wrap up
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