The Hitchhiker's Guide to the Cloud
summary
Compares AWS, Google Cloud and Azure by actually scraping news homepages (screenshot, extracted text, child images) and running them through cloud AI APIs; uses Google Cloud Vision and Natural Language client libs, Azure Cognitive Services (vision + text analytics), and AWS Rekognition and Comprehend. Finds Google’s APIs easiest to call and richest in output, Azure works but forces awkward paragraph-by-paragraph or heavy Docker quickstarts, and AWS sentiment shows surprising failures on short inputs; notes platform-level tools like SageMaker, ML Engine and ML Studio for model training.
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chapters (7)
- 0:00Start
- 11:03Resource Management Template
- 11:35Power Bi
- 16:40Security Identity
- 23:56Ai Machine Learning Api
- 32:40Microsoft Azure
- 38:19About Aws
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