Build Your Own Recommendation Engine on AWS - PART 2 | S02 E28 | Build On Weekly
Did you ever want to build your own recommendation engine powered by machine learning? A way to properly create recommendations for your customers? In PART 2, Piyali, Rohini and Darko deploy the other side of this project, actually hosting the model on Amazon Sagemaker.
You may recall last time Piyali was on Build On Weekly, we talked about why and how do you build recommendation engines. On top of that we cleaned up a lot of data, this time it's time to build this ML model and host it somewhere. In this epsiode we do just that - deploy this Machine Learning model to an endpoint and start serving recommendations back to a front end. Well, we do not have the front end yet - but do join us in the future for PART 3, where we build that front end and make it available to you! 👏
Oh yeah, and if you wish to follow along at home, Piyali was amazing and she wrote a whole blog post on this same topic. You can check it out here.
Check out the recording here:
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