This is a workshop tailored for technical folks without prior data science knowledge, to learn hands-on about AI and ML in AWS. Includes an overview of algorithms and the concepts of data collection and prep., and on a practical level AWS services such as: Sagemaker, Rekognition, Comprehend & Transcribe.
Bruno Amaro Almeida [ brunoamaro.com ]
AI and Machine Learning are key areas of investment, growth and differentiation for many companies. In recent years cloud technologies and managed services made building solutions using AI/ML affordable and easy to experiment with, propelling it’s fast adoption and lowering the barrier to engineers and data enthusiasts.
In this workshop, tailored for engineer and other technical folks without prior data science knowledge, we will learn hands-on about AI and Machine Learning in AWS. We will have an overview of algorithms and the concepts of data collection and preparation. In a practical level, we will explore different AWS managed services for data science with different levels of abstraction, such as AWS SageMaker - the AI/ML Platform - but also the pre-trained AI/ML model APIs with ready-made capabilities such as AWS Transcribe (Speech-to-Text), Rekognition ( Image & Video Classification) and Comprehend ( Sentiment Analysis ).
You need to have the following:
- (required) An AWS account with a user with full rights (admin)
- (preferred) Python 3 installed on your laptop
- (preferred) AWS CLI installed on your laptop
- (optional) a GitHub account
Slide deck : Coming soon
- Getting started with AWS Sagemarker using the AWSLabs unlabelled MNIST K-Means example
- Exploring AWS Rekognition
- Exploring AWS Compreend