7 PM – AI/ML – Darin

Today’s Activities:

1. Reviewed finals projects, debugged streamlit and dataset related issues.
2. Continued the Boston Housing Price Prediction!

Homework:

NOTE: please click on save version for your respective final projects on the kaggle page.

NOTE 2: Use these versions across your kaggle and your pycharm:

!pip install --force-reinstall --no-cache-dir numpy==1.26.4 scipy==1.15.3 matplotlib==3.7.2 fastai==2.7.19 torch==2.6.0 pillow==10.4.0

Part 1:

1. Continue working on your final project.Your goal this week is to train multiple models and deploy them all with the option to choose between different models on streamlit. Upload your latest progress as an ipynb to the google drive.

For those with issues on training the models, do this fix:

!pip install -U "fastprogress==1.0.3"
import fastprogress
print("fastprogress:", fastprogress.__version__)

Then ensure it is 1.0.3, if it isn’t restart the notebook (theres a restart and clear cell output button on the top right of the notebook page).

Notes:

You can reach me at ddjapri@ayclogic.com.

All class notes can be found here.