<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/d30fc3634b4649149f638d4eb3416837&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/d30fc3634b4649149f638d4eb3416837-fe96d020325c8bdd.gif</thumbnail_url><duration>220.337</duration><title>Business Problem</title><description>In this video, I walk you through the process of deploying a sentiment analysis model using a pre-trained model from Hugging Face. We will build an API with FastAPI and containerize it for deployment on AWS Fargate. The goal is to achieve real-time sentiment scoring based on the latest economic news using the Alpaca service. Please pay attention to the concrete steps I outline for fetching the model and setting up the API, as your feedback on this process will be valuable.</description></oembed>