BEGIN:VCALENDAR VERSION:2.0 PRODID:-//American Young Coder - ECPv6.10.1.1//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:American Young Coder X-ORIGINAL-URL:https://www.ayclogic.com X-WR-CALDESC:Events for American Young Coder REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20260308T100000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20261101T090000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260401T190000 DTEND;TZID=America/Los_Angeles:20260401T200000 DTSTAMP:20260721T100407 CREATED:20260402T103452Z LAST-MODIFIED:20260409T020130Z UID:33059-1775070000-1775073600@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nContinued the first project on Cat vs Dog classification\, doing deployment outside of Kaggle.\n\nHomework:\nPart 1\nIn your pycharm project\, do the following: \n# hw: \n# deploy the streamlit application\nFor the above\, use this code: link \nPart 2\nSet up a github account. \n\nCreate an account at https://github.com/ if you haven’t already.\nGo to the top right on your avatar icon\, and click on repositories.\nClick new at the top right.\nCreate a new repository called AYCLOGIC_WED7PM_AI_ML. Leave all other settings at default\, but make sure the visibility is set to public.\nThen go to the avatar icon once more\, and this time click on settings.\nInside settings\, scroll to the very bottom and on the menu bar you should select “Developer Settings“.\nOnce in Developer Settings\, click on Personal Access Tokens (Tokens Classic).\nThen click on “Generate New Token (classic)”.\nSet expiration to 90 days\, and tick “admin:org” and “write:packages“.\nSave the newly generated token but don’t share it!\nThen go back to your pycharm and go to the terminal and follow these instructions:\n\ngit init\n\ngit add .\n\ngit commit -m "Initial Commit"\n\ngit remote add origin https://github.com//AYCLOGIC_WED7PM_AI_ML.git\n\ngit branch -M main\n\ngit push -u origin main\n\n#######################################################\n\nNote that for the above\, you plug in the github username you created before.\n\nUpon executing the commands\, you will be asked to login:\n1. For username\, you can type in your github username\n2. For password\, copy and paste in your personal access token.\n\nNote: When typing in the username and password\, you won't see any characters typed out which is actually a security feature\, but it is there\n\nExtra note: If you get an error saying git is unavailable\, you will need to install it. Email me if this is the case\n\n\n\nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-18/ CATEGORIES:AI/ML,Python Class END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260406T190000 DTEND;TZID=America/Los_Angeles:20260406T200000 DTSTAMP:20260721T100407 CREATED:20260406T234352Z LAST-MODIFIED:20260407T065604Z UID:33088-1775502000-1775505600@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nReviewed finals projects\, debugged streamlit and dataset related issues.\nFinished the Titanic Survival Rate Prediction Problem!\n\nHomework:\nNOTE: please click on save version for your respective final projects on the kaggle page. \nNOTE 2: Use these versions across your kaggle and your pycharm: \n!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\nPart 1:\n\nContinue 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.\n\nFor those with issues on training the models\, do this fix: \n!pip install -U "fastprogress==1.0.3"\nimport fastprogress\nprint("fastprogress:"\, fastprogress.__version__)\nThen 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). \nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-19/ CATEGORIES:AI/ML,Python Class END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260408T190000 DTEND;TZID=America/Los_Angeles:20260408T200000 DTSTAMP:20260721T100407 CREATED:20260409T074439Z LAST-MODIFIED:20260409T074936Z UID:33126-1775674800-1775678400@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nStarted the new project on Multi-class Classification\nWent over deployment code using streamlit\n\nHomework:\nContinuing off of last week if you haven’t already: \nPart 1\nIn your pycharm project\, do the following: \n# hw: \n# deploy the streamlit application\n\n# you have to ensure to use these installs on kaggle:\n\n!pip install --force-reinstall --no-cache-dir \\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\nthen on your pycharm in your requirements.txt you must use:\n\n\n\nstreamlit==1.40.1\nnumpy==1.26.4\nscipy==1.15.3\nmatplotlib==3.9.2\npillow==10.4.0\nfastai==2.7.19\n\n# pip install -r requirements.txt\n\nFor the above\, use this code: link \nPart 2\nSet up a github account. \n\nCreate an account at https://github.com/ if you haven’t already.\nGo to the top right on your avatar icon\, and click on repositories.\nClick new at the top right.\nCreate a new repository called AYCLOGIC_WED7PM_AI_ML. Leave all other settings at default\, but make sure the visibility is set to public.\nThen go to the avatar icon once more\, and this time click on settings.\nInside settings\, scroll to the very bottom and on the menu bar you should select “Developer Settings“.\nOnce in Developer Settings\, click on Personal Access Tokens (Tokens Classic).\nThen click on “Generate New Token (classic)”.\nSet expiration to 90 days\, and tick “admin:org” and “write:packages“.\nSave the newly generated token but don’t share it!\nThen go back to your pycharm and go to the terminal and follow these instructions:\n\ngit init\n\ngit add .\n\ngit commit -m "Initial Commit"\n\ngit remote add origin https://github.com//AYCLOGIC_WED7PM_AI_ML.git\n\ngit branch -M main\n\ngit push -u origin main\n\n#######################################################\n\nNote that for the above\, you plug in the github username you created before.\n\nUpon executing the commands\, you will be asked to login:\n1. For username\, you can type in your github username\n2. For password\, copy and paste in your personal access token.\n\nNote: When typing in the username and password\, you won't see any characters typed out which is actually a security feature\, but it is there\n\nExtra note: If you get an error saying git is unavailable\, you will need to install it. Email me if this is the case\n\n\n\nPart 3\nDeploy your application on streamlit online: https://streamlit.io/ \n\nOn the top right click free -> deploy with streamlit community cloud-> log in with github\nProceed to login with your github account\nHit on create app\nUse the github repository you have created and deploy!\n\nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-17/ CATEGORIES:AI/ML,Python Class END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260413T170000 DTEND;TZID=America/Los_Angeles:20260413T180000 DTSTAMP:20260721T100407 CREATED:20260415T213503Z LAST-MODIFIED:20260415T213503Z UID:33177-1776099600-1776103200@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nReviewed finals projects\, debugged streamlit and dataset related issues.\nContinued the Boston Housing Price Prediction!\n\nHomework:\nNOTE: please click on save version for your respective final projects on the kaggle page. \nNOTE 2: Use these versions across your kaggle and your pycharm: \n!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\nPart 1:\n\nContinue 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.\n\nFor those with issues on training the models\, do this fix: \n!pip install -U "fastprogress==1.0.3"\nimport fastprogress\nprint("fastprogress:"\, fastprogress.__version__)\nThen 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). \nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-20/ CATEGORIES:AI/ML,Python Class END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260415T190000 DTEND;TZID=America/Los_Angeles:20260415T200000 DTSTAMP:20260721T100407 CREATED:20260416T032535Z LAST-MODIFIED:20260416T032535Z UID:33183-1776279600-1776283200@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nContinued the new project on Multi-class Classification\nWent over deployment code using streamlit\n\nHomework:\n# Part 1\n# Make sure the streamlit deployment on the web works\n# Ensure the version match between kaggle and pycharm.\n# In the streamlit website\, set the python version to 3.12 \n# Part 2\n# Use the same code as in CatVSDog\, and train your model for multiclass classification \n# After training\, write down the “error rate” in a comment. \n# Also test your model on the custom dog dataset. \nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-21/ CATEGORIES:AI/ML,Python Class END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260420T190000 DTEND;TZID=America/Los_Angeles:20260420T200000 DTSTAMP:20260721T100407 CREATED:20260420T231312Z LAST-MODIFIED:20260420T231312Z UID:33229-1776711600-1776715200@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nFinalized finals projects\, debugged streamlit and dataset related issues.\nContinued the Boston Housing Price Prediction!\n\nHomework:\nNOTE: please click on save version for your respective final projects on the kaggle page. \nNOTE 2: Use these versions across your kaggle and your pycharm: \n!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\nPart 1:\n\nContinue 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.\n\nFor those with issues on training the models\, do this fix: \n!pip install -U "fastprogress==1.0.3"\nimport fastprogress\nprint("fastprogress:"\, fastprogress.__version__)\nThen 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). \nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-22/ CATEGORIES:AI/ML,Python Class END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260422T190000 DTEND;TZID=America/Los_Angeles:20260422T200000 DTSTAMP:20260721T100407 CREATED:20260423T031304Z LAST-MODIFIED:20260423T031304Z UID:33249-1776884400-1776888000@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nContinued the new project on Multi-class Classification\nWent over deployment code using streamlit\n\nHomework:\nUpload a screenshot of the website working (not locally) \nOn the streamlit website\, ensure you chose python 3.12 and that you have pushed the latest code to github with the commands: \ngit add .\ngit commit -m "update"\ngit push origin main\nAnd if pushing doesn’t work: \ngit push origin main --force\nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-23/ CATEGORIES:AI/ML,Python Class END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Los_Angeles:20260427T190000 DTEND;TZID=America/Los_Angeles:20260427T200000 DTSTAMP:20260721T100407 CREATED:20260428T020008Z LAST-MODIFIED:20260428T040007Z UID:33288-1777316400-1777320000@www.ayclogic.com SUMMARY:7 PM – AI/ML – Darin DESCRIPTION:Today’s Activities:\n\nFinalized finals projects\, debugged streamlit and dataset related issues.\nFinished the Boston Housing Price Prediction!\n\nHomework:\n\nGet your app working on the streamlit website! One more thing you have to ensure is that the labeling function exists with the same name on your pycharm script\nWatch this 45 mins recording about Random Forest https://www.simplilearn.com/tutorials/machine-learning-tutorial/random-forest-algorithm\n\n  \nFor Reine\, this code is the fix\, I have tested and verified training: \npath = "/kaggle/input/datasets/vesuvius13/formula-one-cars/Formula One Cars"\n# Get every image under all team folders\nall_files = get_image_files(path)\nprint("Total files before cleaning:"\, len(all_files))\n\nfrom PIL import Image\nfrom pathlib import Path\n\ndef is_valid_image(fn):\n try:\n # First check the image header\n with Image.open(fn) as im:\n im.verify()\n\n # Then actually load/convert it\, because verify() alone can miss some bad files\n with Image.open(fn) as im:\n im.convert("RGB").load()\n\n return True\n\n except Exception as e:\n return False\n\ngood_files = []\nbad_files = []\n\nfor fn in all_files:\n if is_valid_image(fn):\n good_files.append(fn)\n else:\n bad_files.append(fn)\n\nprint("Good files:"\, len(good_files))\nprint("Bad files:"\, len(bad_files))\n\nfor fn in bad_files[:30]:\n print(fn)\ndef extract_brand(fn):\n folder_name = Path(fn).parent.name\n return folder_name.replace(" F1 car"\, "").strip()\n\nprint(extract_brand("/kaggle/input/datasets/vesuvius13/formula-one-cars/Formula One Cars/Racing Point F1 car/00000090.png"))\nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here. URL:https://www.ayclogic.com/event/7-pm-ai-ml-darin-24/ CATEGORIES:AI/ML,Python Class END:VEVENT END:VCALENDAR