This workshop materials are used in Artificial Intelligence and Machine Learning workshop, that focuses on using AWS services. There are 3 labs available:

1. Face Recognition and AI Services
2. Movies Recommender with Factorization Machines on SageMaker
3. Movies Recommender with Amazon Personalize

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Face Recognition and AI Services

This lab will go through:

1. Face detection, face comparison, face search, and text extraction from image using Rekognition with boto3 (AWS Python SDK)
2. Text understanding with Amazon Comprehend
3. Speech syntesis using Amazon Polly
4. Speech to text with Amazon Transcribe
5. Text translation with Amazon Translate
6. Dominant language detection using Amazon Comprehend Lab will be performed in a Jupyter notebook, launched with Amazon SageMaker Notebook Instance feature.

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Movies Recommender with Factorization Machines on SageMaker

The lab focuses in building movies recommender using Factorization Machines technique provided as a built-in algorithm in Amazon SageMaker. The lab covers data fetching and preparation, model training, model deployment, and sample recommendation inference. A Jupyter notebook script is provided to interact with Amazon SageMaker in the whole lab.

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Movies Recommender with Amazon Personalize

The lab provides another way of building movies recommender using Deep Learning via Amazon Personalize. This includes data fetching and uploading to S3, schema and dataset-group creation, data import, solution building (training phase), campaign launching (model deployment), and sample inference. This lab provided both in Jupyter notebook script and step-by-step guidance to interact via AWS UI console.

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Lab Preparation

There is a PDF file ("Lab Preparation.pdf") that contains guidance to setup the Jupyter notebook instance on Amazon SageMaker to start any lab.