Machine Learning and AI in Java on AWS

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" summary

Overview of concrete demos and results: Polly: 50 voices, 24 languages generates real-time SSML speech with one API call; Rekognition: detects up to 15 faces returns bounding boxes, age ranges, emotions and can compare faces for matches. Amazon ML trains and deploys a binary classifier from ~40,000 banking rows to an API endpoint in seconds. EMR + Spark runs a Zeppelin notebook that finds Naive Bayes best for spam; MXNet trains MNIST (60,000 examples) on GPU and scales to hundreds of GPUs. Lex + Lambda pattern handles chatbot routing.

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" chapters (18)

1. 0:00Agenda
2. 1:40What is AI
3. 13:05Object Detection
4. 21:34FraudNet example
5. 22:49Banking example
6. 23:37Building a model
7. 30:01Different use cases
8. 30:22Amazon EMR
9. 31:45Multiple integrations
10. 32:51Spark
11. 34:10Start a Hadoop cluster
12. 41:07Deep learning
13. 41:58MXNet
14. 43:32MXNet Example
15. 48:10Experiments
16. 48:56Recap
17. 49:31Resources
18. 50:10Questions

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