Using AWS Artificial Intelligence services with Python
summary
Shows concrete Python examples using Boto3 and “a dozen lines” to call AWS AI APIs and includes a runnable Jupyter notebook in the repo (2023_0214) with code. Demonstrates Amazon Rekognition for OCR and object/face detection (once finds a nearly invisible third person), Comprehend for sentiment and PII, Polly for text‑to‑speech, Transcribe/Translate and a factory sound‑change detector. Mentions SageMaker/Studio Lab for infra, the free tier offering 1,000 image analyses/month, and notes per‑image costs can rise in production.
AI-written summary · about
chapters (8)
- 0:00Introduction and speaker
- 3:20Defining AI and ML
- 8:45Frameworks and infrastructure
- 14:12Organizational ML services
- 22:17Managed AI services overview
- 28:59Amazon Rekognition demo
- 35:48Code examples and resources
- 38:32Q&A and conclusion
related talks
01h 41mGetting started with Machine Learning on AWS.
55mMachine Learning and AI in Java on AWS
29mSolve common business problems with AI and ML
42mHow to Build Smart Applications Without a Machine Learning Background
51mProfundizando en Aprendizaje Automático para Desarrolladores
48mBuilding Serverless AI powered Applications on AWS
20mAWS On Air ft. Amazon SageMaker Studio Lab
06mAI and machine learning at Amazon