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DTSTART;TZID=America/Los_Angeles:20251205T170000
DTEND;TZID=America/Los_Angeles:20251205T180000
DTSTAMP:20260515T014257
CREATED:20251206T012150Z
LAST-MODIFIED:20251206T013219Z
UID:31816-1764954000-1764957600@www.ayclogic.com
SUMMARY:5 PM – Intro To Python – Darin
DESCRIPTION:Today We Do\n\nWent over final project progress\nCreated a text based game using all the knowledge learnt in class.\n\nHomework\n\nContinue working on the final project\, you need to draw at least four objects as shape functions for this week.\n\nFor Hudson: Convert your drawing such as the car with the use of functions and a new function called drawCar that makes use of drawRectangle\, drawCircle\, etc. \nSubmit the current progress of your thonny drawing to google drive when you are done. \nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here: https://drive.google.com/drive/folders/1ClxGyA_3oLZtwhgN0j3BVZjpffoxMHNj?usp=sharing
URL:https://www.ayclogic.com/event/5-pm-intro-to-python-darin-29/
CATEGORIES:Python Class,Python Level 1
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251205T170000
DTEND;TZID=America/Los_Angeles:20251205T180000
DTSTAMP:20260515T014257
CREATED:20251206T033340Z
LAST-MODIFIED:20251206T033340Z
UID:31820-1764954000-1764957600@www.ayclogic.com
SUMMARY:5 PM – Intro To Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe went over normal functions and functions with return value.\n\nHomework\n(Upload your homework into your Google Drive HW folder a day before the class starts) \n\nMake a new file called “Dec5_Function2_HW.py”\nOn page 131\, do the “Try It Yourself” section.\nDo copy the code from pages 137 – 139.\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/5-pm-intro-to-python-abigail-9/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251205T200000
DTEND;TZID=America/Los_Angeles:20251205T210000
DTSTAMP:20260515T014257
CREATED:20251206T061610Z
LAST-MODIFIED:20251206T061610Z
UID:31822-1764964800-1764968400@www.ayclogic.com
SUMMARY:8 PM - AI and Machine Learning - Joel (Gamas Sub)
DESCRIPTION:Today We Did\n\nWent over each students custom project and help them with the following in their custom kaggle project\n\n\n!pip install --force-reinstall \\n  "numpy==1.26.4" \\n  "scipy==1.15.3" \\n  "matplotlib==3.7.2" \\n  "fastai==2.7.19" \\n  "torch==2.6.0" \\n "pillow==10.4.0"\n\nMost of them chose dataset for their projects where the object names is in the folder name instead of the file name\, but their labeling functions assumes file_name is passed as the function parameter. And they are also using ImageDataLoaders.from_name_func instead of ImageDataLoaders.from_path_func. I assisted with all students to change their functions and to use ImageDataLoaders.from_path_func except for Aiden and Joshua because their datasets have both the name of the object in both folder and filename.\n\n\nSetup Titanic Survival streamlit pycharm project and asked them to install requirements.txt\n\n\n\nfastai==2.8.4\nnumpy==1.26.4\nscipy==1.13.1\nstreamlit==1.52.1\n\n\n\n\n\nHomework\nContinue with your custom projects \nFOR ALL STUDENTS\n\nin your streamlit pycharm projects\, make sure you add this file requirements.txt AND make sure it has the following content\n\n\n\nstreamlit==1.40.1\nnumpy==1.26.4\nscipy==1.14.1\nmatplotlib==3.9.2\npillow==10.4.0\ntorch==2.6.0\nfastai==2.7.19\n\n\n\n\nOpen terminal and run\n\n\npip install -r requirements.txt\n\n\n\n\nFor Individual Students\n\nAiden\n\nTrain your model until you get small enough error_rate. Sometimes because of bad data set\, small error_rate might not be possible.\nexport your pkl file from Kaggle to your computer and start your Pycharm streamlit project.\n\n\nRussell\n\nFix your Kaggle labelling function so it can extract object name from the folder name instead of file name. Look at how we did this in single digit prediction project.\nUtilize ImageDataLoaders.from_path_func instead of from_name_func\nExport pkl file and start your Pycharm streamlit project.\n\n\nJoshua\n\nYour project is pretty far (both Kaggle and Pycharm)\, which is good. Since we just fixed the fastai function in your Kaggle to 2.7.19\, reexport your PKL file.\nDownload the PKL file from Kaggle to your computer and to your Pycharm.\nDo some streamlit testing.\n\n\nRafael\n\nFix your Kaggle labelling function so it can extract object name from the folder name instead of file name. Look at how we did this in single digit prediction project.\nUtilize ImageDataLoaders.from_path_func instead of from_name_func\nExport pkl file and start your Pycharm streamlit project.
URL:https://www.ayclogic.com/event/8-pm-ai-and-machine-learning-joel-gamas-sub/
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