English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 3h 07m | 528 MB
Amazon Web Services (AWS) offers a wealth of services and tools that help data scientists leverage machine learning to craft better, more intelligent solutions. In this course, learn about patterns, services, processes, and best practices for designing and implementing machine learning using AWS. Instructor Lynn Langit takes a look at general machine learning concepts, including key machine learning algorithm types. She also examines available service types, such as AWS Machine Learning, Lex, Polly, and Rekognition, which you can use to predict image and video labels. Plus, she steps through how to work with platforms like AWS SageMaker, which includes hosted Jupyter notebooks.
Topics include:
- How machine learning is used in analytics
- AWS AI servers vs. platforms
- Predicting using Polly text-to-speech
- Predicting using Rekognition for video
- Using Lex to build a conversational application
- Using the AWS Machine Learning service to train, host, and predict
- Working with MXNet in Databricks
- Working with EMR for machine learning
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