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At the end of any project, it's essential to look back and ask two questions: What went well? and What could be improved? In this video, I ask these questions looking back on my machine learning project to replicate Airbnb's amenity detection.
If you're not sure what's going on, make sure to check out the rest of the videos in the series.
Now this project is over, it's time to move onto the next one!
Links:
My machine learning course - dbourke.link/mlcourse
Blog post version of the project - www.mrdbourke.com/airbnb-amen...
Example code on Google Colab - dbourke.link/airbnbcode
Code on GitHub - github.com/mrdbourke/airbnb-a...
All of my notes/ideas in Notion - dbourke.link/airbnb42days
Airbnb Amenity Detection article - / 05qperz3a4
Check it out for yourself - airbnb-amenity-detection.apps... (note: may be taken down due to hosting costs)
All videos in this series:
Full playlist - dbourke.link/airbnbplaylist
Part 1 (overview) - • Using Machine Learning...
Part 2 (data exploration) - • Using Machine Learning...
Part 3 (data manipulation) - • Replicating Airbnb's M...
Part 4 (building a small dog model) - • I got Detectron2 worki...
Part 5 (experiment tracking) - • Every model I build ha...
Part 6 (modelling experimentation) - • 34,835 training images...
Part 7 (building a big dog model) - • Results from 18-hours ...
Part 8 (getting my modelling deployed) - • I got my machine learn...
Part 9 (project wrap up and retrospective) - • What could be improved...
Note: I am not affiliated with Airbnb nor are they involved with this series of videos in any way.
Connect elsewhere:
Email updates on my work - dbourke.link/newsletter
Web - dbourke.link/web
Quora - dbourke.link/quora
Medium - dbourke.link/medium
Twitter - dbourke.link/twitter
LinkedIn - dbourke.link/linkedin
#machinelearning #datascience #deeplearning