Today is Day 1 of learning AI and Data Pipelines! 🤖
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I’ve been wanting to get into algorithms for awhile now, especially from a deployment and retraining perspective. And ChatGPT is too cool not to try and understand what’s going on behind the scenes, amirite? 👀
For me, Day 1 mainly focused on getting up to speed on:
- what you can do with AWS SageMaker, a robust framework and studio for working with AI, models, datasets, and more.
- learning the various aspects of a ML pipeline, beyond just the algorithm, and I included a helpful flowchart in the video for reference.
- studying how the various technologies interact in the cloud, such as using Amazon S3 for fast reads/writes of your data and Amazon SageMaker as the manager and endpoint of our workflow.
- checking out Kaggle as a dataset online library for open sourced information to use.
It was surprising to learn how many steps go into #machinelearning systems than just the algorithm. Let’s explore why!
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