Machine Learning for Developers
summary
Overview of machine learning basics, tooling and a working demo that ties model, voice and cloud together. Covers supervised vs unsupervised vs reinforcement learning, convolutional and recurrent nets, transfer learning and GANs, and practical hardware choices like EC2 P2 with Nvidia K80 GPUs and FPGA instances. Demos use MXNet, Amazon Rekognition, Polly and Amazon Lex to power an Alexa skill predicting bike demand that forecasts 312 bikes tomorrow at 8:00am (44 casual / 268 registered). Advice: use managed APIs when available and validate models with train/validation/test splits.
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chapters (4)
- 0:00Start
- 41:35Amazon Rekognition Image Recognition And Analysis Powered By Deep Learning
- 44:41Amazon Polly Text To Speech Powered By Deep Leaming
- 48:29Amazon Machine Learning Create ML models without having to learn complex algorithm and technology
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