| 00d3a938-cdc9-4b94-9819-b12bb3505239.jpg?042148 | 126.4 KB | ||
| 1 - Introduction and App Overview.mp4 | 21.7 MB | ||
| 10 - Asynchronous Model Serving with FastAPI.mp4 | 66.9 MB | ||
| 11 - Updating the UI to respond to the async server.mp4 | 61.7 MB | ||
| 12 - Conclusion and Final Remarks.mp4 | 7.7 MB | ||
| 13 - Final Code.html | 409.6 B | ||
| 2 - FastAPI and Streamlit for Machine Learning Overview.mp4 | 13.5 MB | ||
| 3 - Docker Installation Guide.mp4 | 25.4 MB | ||
| 4 - Final Code.html | 409.6 B | ||
| 5 - Project Setup.mp4 | 45.5 MB | ||
| 5fa5d40f-740b-4e8f-8dfb-c83af106f62c.jpg?042148 | 169.8 KB | ||
| 5fa5d40f-740b-4e8f-8dfb-c83af106f62c_composition_vii.jpg?042148 | 212.7 KB | ||
| 6 - FastAPI Backend and Image Transformation Functionality.mp4 | 132.3 MB | ||
| 7 - Docker Container Setup.mp4 | 23.3 MB | ||
| 8 - Developing the Streamlit User Interface.mp4 | 54.7 MB | ||
| 9 - Docker Compose Setup.mp4 | 48.7 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Dockerfile | 204.8 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| candy.t7 | 14.8 MB | ||
| composition_vii.t7 | 27.1 MB | ||
| config.py | 307.2 B | ||
| docker-compose.yml | 307.2 B | ||
| download_models.sh | 512 B | ||
| feathers.t7 | 17.6 MB | ||
| gabriel-ramos.jpg?042148 | 2.3 MB | ||
| inference.py | 1.1 KB | ||
| la_muse.t7 | 24.3 MB | ||
| main.py | 1.8 KB | ||
| man_jumping.jpg?042148 | 1.5 MB | ||
| mosaic.t7 | 17.6 MB | ||
| requirements.txt | 0 B | ||
| starry_night.t7 | 24.3 MB | ||
| the_scream.t7 | 17.6 MB | ||
| the_wave.t7 | 24.3 MB | ||
| udnie.t7 | 10.7 MB | ||
| ▲ 63 total files | |||
Machine Learning Models With Fastapi, Streamlit And Docker
https://DevCourseWeb.com
Published 3/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 764.33 MB | Duration: 1h 4m
Learn how to serve a machine learning model with FastAPI, Streamlit and Docker
What you'll learn
Develop an asynchronous API with Python and FastAPI
Serve up a machine learning model with FastAPI
Develop a UI with Streamlit
Containerize FastAPI and Streamlit with Docker
Leverage asyncio to execute code in the background outside the request/response flow
Requirements
Intermediate Python Skills
Intermediate Docker Skills
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