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X-ORIGINAL-URL:https://www.ayclogic.com
X-WR-CALDESC:Events for American Young Coder
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TZID:America/Los_Angeles
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TZOFFSETFROM:-0800
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TZNAME:PDT
DTSTART:20260308T100000
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DTSTART:20261101T090000
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260715T190000
DTEND;TZID=America/Los_Angeles:20260715T200000
DTSTAMP:20260720T091101
CREATED:20260716T075317Z
LAST-MODIFIED:20260716T075317Z
UID:34166-1784142000-1784145600@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nContinued the Boston Housing Prediction project!\n\nHomework:\n\n\n\n\n\n\nWatch this video: https://www.youtube.com/watch?v=1aM1KYvl4Dw \n\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-34/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260708T190000
DTEND;TZID=America/Los_Angeles:20260708T200000
DTSTAMP:20260720T091101
CREATED:20260716T010622Z
LAST-MODIFIED:20260716T010622Z
UID:34162-1783537200-1783540800@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nStarted the Boston Housing Prediction project\n\nHomework:\n\n\n\n\n\n\nWatch this video by next week! https://www.ayclogic.com/event/7-pm-ai-machine-learning-gamas-13/ \n\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-33/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260627T123000
DTEND;TZID=America/Los_Angeles:20260627T133000
DTSTAMP:20260720T091101
CREATED:20260627T203633Z
LAST-MODIFIED:20260627T215518Z
UID:34011-1782563400-1782567000@www.ayclogic.com
SUMMARY:12:30 PM – Intro to Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe reviewed all the coding topics to prepare for the test.\n\nHomework\n\nNo homework\, just study for your Final Test!\nStudy\n\nTurtle projects\nGrocery Shopping Cart\nRobux Shopping Cart\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com \n 
URL:https://www.ayclogic.com/event/1230-pm-intro-to-python-abigail-11/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260622T173000
DTEND;TZID=America/Los_Angeles:20260622T183000
DTSTAMP:20260720T091101
CREATED:20260623T013859Z
LAST-MODIFIED:20260623T013859Z
UID:33953-1782149400-1782153000@www.ayclogic.com
SUMMARY:5:30 PM – Intro to Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe started working on the Robux Balance Program.\n\nHomework\n(Upload your homework into your Google Drive HW folder a day before the class starts) \n\nAfter the user exits the program\, list out all of the items they bought.\n\nMake sure to list out each item with a number next to the item.\nOutput should look like this:\n\nYou have purchased the following items:\n1. Hat\n2. Hair\n3. Hair\n4. VIP Server\n\n\n\nWhen adding robux\, ask user how much they want to add. Then\, add that amount.\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/530-pm-intro-to-python-abigail-13/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260618T200000
DTEND;TZID=America/Los_Angeles:20260618T210000
DTSTAMP:20260720T091101
CREATED:20260619T041227Z
LAST-MODIFIED:20260624T055311Z
UID:33917-1781812800-1781816400@www.ayclogic.com
SUMMARY:8 PM – Advanced AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nContinued the glasses project on google colab.\nDeployed to streamlit.\n\nHomework:\n\n\n\nComplete this notebook which involves writing a convolution function! https://drive.google.com/file/d/1XzoqPXFm8_N5MlciZXVi5anVD8InXdRP/view?usp=sharing\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/8-pm-advanced-ai-ml-darin-5/
CATEGORIES:Advanced AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260615T173000
DTEND;TZID=America/Los_Angeles:20260615T183000
DTSTAMP:20260720T091101
CREATED:20260616T013947Z
LAST-MODIFIED:20260616T013947Z
UID:33868-1781544600-1781548200@www.ayclogic.com
SUMMARY:5:30 PM - Intro to Python - Abigail
DESCRIPTION:Today We\n\n\n\n\nWe finished the Kaleido Spiral Project.\nWe started working on the Shopping Cart Project.\n\nHomework\n(Upload your homework into your Google Drive HW folder a day before the class starts) \n\nFind a second way to print out all the items in the shopping_cart list using a for loop. (You cannot use for i in range())\nAdd a wallet feature:\n\nIn the beginning of the loop you should ask the user how much money they have. This question should NOT be continuously asked over and over.\nEvery time a user buys an item\, the wallet money should decrease depending on the price of the item.\nIf the user does not have enough money to purchase the item\, it should print out “Insufficient Money.”\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/530-pm-intro-to-python-abigail-12/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260613T123000
DTEND;TZID=America/Los_Angeles:20260613T133000
DTSTAMP:20260720T091101
CREATED:20260613T205948Z
LAST-MODIFIED:20260613T205948Z
UID:33854-1781353800-1781357400@www.ayclogic.com
SUMMARY:12:30 PM – Intro To Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe finished the Kaleido Spiral Project.\nWe started working on the Shopping Cart Project.\n\nHomework\n(Upload your homework into your Google Drive HW folder a day before the class starts) \n\nUpload your Turtle Project today by 11:59 PM to fix your project. This is optional\, but highly recommended to get a better score on your project.\n\nEthan:\n\nFix the lettering code.\nChange the name of your “t” and “r” functions to not throw any errors\nFix the code in your “r”\nRemove any duplicate/redundant code you have.\n\n\nEmma:\n\nRemove any duplicate/redundant code you have.\n\n\n\n\nIn your Shopping Cart project\, continuously ask the user to input the menu options (1\,2\,3\,or 4).\n\nIf user enters 1\, print “milk”\nif user enters 2\, print “eggs”\nif user enters 3\, print “chips”\nif user enter 4\, print “bye bye” and stop asking user\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/1230-pm-intro-to-python-abigail-10/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260611T200000
DTEND;TZID=America/Los_Angeles:20260611T210000
DTSTAMP:20260720T091101
CREATED:20260612T025106Z
LAST-MODIFIED:20260612T040314Z
UID:33821-1781208000-1781211600@www.ayclogic.com
SUMMARY:8 PM – Advanced AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nStarted the glasses project on google colab\n\nHomework:\n\n\nWatch the following video for more information and write your answers to a file called Jun4_CNN_HW1.txt. Upload to google drive when you are done: \n\nWhy does a CNN use multiple filters instead of just one?\nWhat is pooling\, and why is it useful?Explain max pooling in simple terms.\nWhy can CNNs recognize an object even if it moves slightly in the image?\nImagine you are building a CNN to recognize cats and dogs. What simple features might the CNN learn first? What more complex features might it learn later?\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/8-pm-advanced-ai-ml-darin-4/
CATEGORIES:Advanced AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260610T190000
DTEND;TZID=America/Los_Angeles:20260610T200000
DTSTAMP:20260720T091101
CREATED:20260611T032816Z
LAST-MODIFIED:20260611T032816Z
UID:33813-1781118000-1781121600@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nContinued the titanic survival project\n\nHomework:\n\nChoosing what you want to classify — Can be anything in real life\, the only thing is you have to make sure the data exists on Kaggle. \nThe project has to be able to classify at least 5 different categories. \nWhat we did last week: \n\nSet up the labelling function\nVerify Dataloader works with .show_batch() (reference old code for how to do this\, it will depend on how you extract labels\, whether its via path or filename)\nRun training with a vision_learner.\nUse the proper imports (fast ai 2.7.19)\nUse lr.find() to get the proper learning rate\, then run finetuning with the discovered value (you must only call fine_tune once!)Add the following into the vision learner to ensure lr_find works!:\npath=Path(“/kaggle/working”)\,\nmodel_dir=”models”\,\nExport the file as a .pkl file onto your computer!\n\nWhat you have to do next week: \n\nMake sure training used the proper installs and library versions!\nRerun exporting the .pt file and save it from the outputs on the right of the kaggle page\nUse your exported .pt file on streamlit and deploy on the website https://streamlit.io/Details are as follows below:\n\n\n\nDetails on how to deploy on streamlit:\n\nSet up a github account. \n❌ means skip unless you lost it\, ✅ means do \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_FINAL_PROJECT. 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/<your username>/AYCLOGIC_WED7PM_AI_ML_FINAL_PROJECT.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\nFinally after all this you should be able to go to streamlit.io -> top right -> free -> login with github -> choosing your own github repository -> modifying the settings to do python 3.12 -> deploy \nNote it is important you train your model with the downgraded versions (uncomment them)\, then after running the pip install proceed by hitting Run -> Restart & Clear Cell Outputs before proceeding with the other blocks. Make sure your imports match the pip installs\, then finally export the model and download it from /kaggle/working on the right side of the website (may need to hit on refresh – the circular arrows on the right of /kaggle/working) \n\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-31/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260604T200000
DTEND;TZID=America/Los_Angeles:20260604T210000
DTSTAMP:20260720T091101
CREATED:20260605T022740Z
LAST-MODIFIED:20260605T042046Z
UID:33762-1780603200-1780606800@www.ayclogic.com
SUMMARY:8 PM – Advanced AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nFinished the YOLO project\, did multiclass classification on web cam feed or pre-recorded videos.\n\nHomework:\n\n\nWatch the following video and write your answers to a file called Jun4_CNN_HW1.txt. Upload to google drive when you are done: \n\nWhat does CNN stand for\, and what type of data is it especially good at working with?\nWhy is it hard for a regular neural network to understand images?Hint: Think about how many pixels an image has.\nWhat is a filter/kernel in a CNN?Explain it in your own words.\nWhat kind of “features” might early CNN filters detect in an image?\nWhat is a feature map?\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/8-pm-advanced-ai-ml-darin-3/
CATEGORIES:Advanced AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260603T190000
DTEND;TZID=America/Los_Angeles:20260603T200000
DTSTAMP:20260720T091101
CREATED:20260604T034205Z
LAST-MODIFIED:20260604T034205Z
UID:33749-1780513200-1780516800@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nFinished the Single Digit Classifier project.\n\nHomework:\n\nChoosing what you want to classify — Can be anything in real life\, the only thing is you have to make sure the data exists on Kaggle. \nThe project has to be able to classify at least 5 different categories. \nWhat we did last week: \n\nSet up the labelling function\nVerify Dataloader works with .show_batch() (reference old code for how to do this\, it will depend on how you extract labels\, whether its via path or filename)\nRun training with a vision_learner.\nUse the proper imports (fast ai 2.7.19)\nUse lr.find() to get the proper learning rate\, then run finetuning with the discovered value (you must only call fine_tune once!)Add the following into the vision learner to ensure lr_find works!:\npath=Path(“/kaggle/working”)\,\nmodel_dir=”models”\,\nExport the file as a .pkl file onto your computer!\n\nWhat you have to do next week: \n\nMake sure training used the proper installs and library versions!\nRerun exporting the .pt file and save it from the outputs on the right of the kaggle page\nUse your exported .pt file on streamlit and deploy on the website https://streamlit.io/\nDetails are as follows below:\n\n\n\nDetails on how to deploy on streamlit:\n\nSet up a github account. \n❌ means skip unless you lost it\, ✅ means do \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_FINAL_PROJECT. 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/<your username>/AYCLOGIC_WED7PM_AI_ML_FINAL_PROJECT.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\nFinally after all this you should be able to go to streamlit.io -> top right -> free -> login with github -> choosing your own github repository -> modifying the settings to do python 3.12 -> deploy \n\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-30/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260602T190000
DTEND;TZID=America/Los_Angeles:20260602T200000
DTSTAMP:20260720T091101
CREATED:20260603T032406Z
LAST-MODIFIED:20260603T032406Z
UID:33739-1780426800-1780430400@www.ayclogic.com
SUMMARY:7 PM – Python Game Development – Bill (Darin Sub)
DESCRIPTION:Today We:\n\nContinued the shoot balloon project\nMade the target out of lines and circles\nMade collisions between balloon and target\n\nYour HW:\n\nIf you haven’t already: Buy your assets off of graphic river and audio jungle (websites in last week’s event)\nRefine the project plans based on comment feedback\nStart making progress with Week 1 of your plan in the newly cloned repo’s. Push and commit when you are done!
URL:https://www.ayclogic.com/event/7-pm-python-game-development-bill-darin-sub/
CATEGORIES:Python Class,Python Game Development
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260601T173000
DTEND;TZID=America/Los_Angeles:20260601T183000
DTSTAMP:20260720T091101
CREATED:20260602T014339Z
LAST-MODIFIED:20260602T014339Z
UID:33719-1780335000-1780338600@www.ayclogic.com
SUMMARY:5:30 PM - Intro to Python - Abigail
DESCRIPTION:Today We\n\n\n\n\nWe went over more turtle functions.\nWe learned how to draw circles and understand set heading.\n\nHomework\n(Upload your homework into your Google Drive HW folder a day before the class starts) \n\nEthan:\n\nCall your right_arm & left_arm functions inside the cactus function instead of calling them separately.\nChange the code inside your cactus function to use the rectangle function.\nPut your cloud circle function calls inside a function called cloud.\n\n\nEmma:\n\nGet rid of one of the mountain functions. You only need one.\nReplace your draw_tree_trunk and draw_land function with the rectangle function call.\nUse your dot function to make the sun.\n\n\nBoth:\n\nOverall\, your projects look very good. You just have to make use of your rectangle and circle functions\, because you made them but aren’t using them enough.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/530-pm-intro-to-python-abigail-11/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260530T123000
DTEND;TZID=America/Los_Angeles:20260530T133000
DTSTAMP:20260720T091101
CREATED:20260530T214933Z
LAST-MODIFIED:20260530T214933Z
UID:33694-1780144200-1780147800@www.ayclogic.com
SUMMARY:12:30 PM - Intro to Python - Abigail
DESCRIPTION:Today We\n\n\n\n\nWe went over more Python Turtle applications.\n\nHomework\n\nContinue working on your Turtle project.\nHere are the instructions + the other students projects for inspiration: https://www.ayclogic.com/intro-to-python-final-project-criteria/\n\n\n\n\n\n\n\n\n\n\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/1230-pm-intro-to-python-abigail-9/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260528T200000
DTEND;TZID=America/Los_Angeles:20260528T210000
DTSTAMP:20260720T091101
CREATED:20260529T025026Z
LAST-MODIFIED:20260529T040419Z
UID:33676-1779998400-1780002000@www.ayclogic.com
SUMMARY:8 PM – Advanced AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nIntroduced course projects\, and began diving into project 1 – YOLO Live Object Classification\nStreamed videos in proper format (BGR2RGB conversion)\n\nHomework:\n\n\nAdd 3 more classifications onto your human_detection_v2 to get a total of 4 classifications on your own cameras. \nUse this as reference for the classes: https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml \n\n\nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here.
URL:https://www.ayclogic.com/event/8-pm-advanced-ai-ml-darin-2/
CATEGORIES:Advanced AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260527T190000
DTEND;TZID=America/Los_Angeles:20260527T200000
DTSTAMP:20260720T091101
CREATED:20260528T032207Z
LAST-MODIFIED:20260604T021216Z
UID:33669-1779908400-1779912000@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nFinished the Single Digit Classifier project.\n\nHomework:\nFor Rexford\, choose the dataset for your project (has to be multiclass\, and catch up the below) \n\nHW 1: \n\nChoosing what you want to classify — Can be anything in real life\, the only thing is you have to make sure the data exists on Kaggle. \nThe project has to be able to classify at least 5 different categories. \nWhat we did last week: \n\nSet up the labelling function\nVerify Dataloader works with .show_batch() (reference old code for how to do this\, it will depend on how you extract labels\, whether its via path or filename)\nRun training with a vision_learner.\nUse the proper imports (fast ai 2.7.19)\nUse lr.find() to get the proper learning rate\, then run finetuning with the discovered value (you must only call fine_tune once!)Add the following into the vision learner to ensure lr_find works!:\npath=Path(“/kaggle/working”)\,\nmodel_dir=”models”\,\nExport the file as a .pkl file onto your computer!\n\nWhat you have to do next week: \n\nUse your exported .pt file on streamlit and deploy on the website https://streamlit.io/\n\n\nHW 2 (if you haven’t done so already): \nDownload the following CSV file: https://drive.google.com/file/d/1kP6A9y0UBssOg3Exunv9Mnmilb0657Sh/view \nThen do the following in a new notebook called WED-7PM-PandasHW1: \n\nLoad the data\nShow only the Channel and Subscribers columns\nFind channels with more than 2000 subscribers\nFor this you can use something like this:df[df[“Math”] > 80]\,but of course for this data.\nAdd a new column Subs_per_Video\nAnswer the question in Markdown\, which channel is the most efficient?\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-29/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260521T200000
DTEND;TZID=America/Los_Angeles:20260521T210000
DTSTAMP:20260720T091101
CREATED:20260526T183404Z
LAST-MODIFIED:20260526T213530Z
UID:33632-1779393600-1779397200@www.ayclogic.com
SUMMARY:8 PM – Advanced AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nIntroduced course projects\, and began diving into project 1 – YOLO Live Object Classification\nStreamed videos in proper format (BGR2RGB conversion)\n\nHomework:\nWhen you are done\, submit your file and any images into the same google drive from the intro to ML/AI! \n\n\nWatch this video: https://www.youtube.com/watch?v=aircAruvnKk\nCreate a new directory in your Advanced AI PyCharm project called HW\nCreate a May21_HW.py and answer the following questions:\nQ1. Within a neural network\, how does one layer lead to the input of a single neuron in the next layer? (hint: think about how you get the value for the input of the neuron\, and its range) \nQ2. If the output from one layer (after aggregating all neurons) is 0.7\, what is the value after using the sigmoid activation function? \nQ3. Write code for implementing the sigmoid function in python using numpy. (hint: use np.exp() for the exponential function) \nFinally\, test your function above with input 0.7 and double check that it matches your answer from Q2. Paste a screenshot of your program working and submit to the google drive when you are finished.\n\n\nNotes:\nYou can reach me at ddjapri@ayclogic.com. \nAll class notes can be found here.
URL:https://www.ayclogic.com/event/8-pm-advanced-ai-ml-darin/
CATEGORIES:Advanced AI/ML,Advanced AI/ML
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260520T190000
DTEND;TZID=America/Los_Angeles:20260520T200000
DTSTAMP:20260720T091101
CREATED:20260521T034953Z
LAST-MODIFIED:20260521T040109Z
UID:33607-1779303600-1779307200@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nFinished the Single Digit Classifier project.\n\nHomework:\nFor Rexford\, choose the dataset for your project (has to be multiclass\, and catch up the below) \n\nHW 1: \n\nChoosing what you want to classify — Can be anything in real life\, the only thing is you have to make sure the data exists on Kaggle. \nThe project has to be able to classify at least 5 different categories. \nWhat we did last week: \n\nSet up the labelling function\nVerify Dataloader works with .show_batch() (reference old code for how to do this\, it will depend on how you extract labels\, whether its via path or filename)\nRun training with a vision_learner.\n\nWhat you have to do next week: \n\nUse the proper imports (fast ai 2.7.19)\nUse lr.find() to get the proper learning rate\, then run finetuning with the discovered value (you must only call fine_tune once!)\nAdd the following into the vision learner to ensure lr_find works!:\npath=Path(“/kaggle/working”)\,\nmodel_dir=”models”\,\nExport the file as a .pt file onto your computer!\n\n\nHW 2: \nDownload the following CSV file: https://drive.google.com/file/d/1kP6A9y0UBssOg3Exunv9Mnmilb0657Sh/view \nThen do the following in a new notebook called WED-7PM-PandasHW1: \n\nLoad the data \nShow only the Channel and Subscribers columns \nFind channels with more than 2000 subscribers\nFor this you can use something like this:  \ndf[df[“Math”] > 80]\,but of course for this data. \n \nAdd a new column Subs_per_Video \nAnswer the question in Markdown\, which channel is the most efficient?\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-28/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260518T173000
DTEND;TZID=America/Los_Angeles:20260518T183000
DTSTAMP:20260720T091101
CREATED:20260519T021906Z
LAST-MODIFIED:20260519T021906Z
UID:33568-1779125400-1779129000@www.ayclogic.com
SUMMARY:5:30 PM – Intro to Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe started working on the turtle faces project.\n\nHomework\n(Upload your homework into your Google Drive HW folder a day before the class starts) \n\nDo your homework in your may18_faces.py file.\nMake a new function called faces2.\n\nIt will have 4 parameters (x\, y\, face_color\, eye_color)\nMake the face look like the image below:\n\n\n\nWhen you call the faces2 function\, have the face_color and eye_color be randomized colors.\n\nrandomized colors include red\, blue\, yellow\, orange\, green\, and purple.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/530-pm-intro-to-python-abigail-10/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260514T190000
DTEND;TZID=America/Los_Angeles:20260514T200000
DTSTAMP:20260720T091101
CREATED:20260515T030411Z
LAST-MODIFIED:20260515T030613Z
UID:33509-1778785200-1778788800@www.ayclogic.com
SUMMARY:7 PM – Intro to Python – Joshua (Darin Sub)
DESCRIPTION:Today we did:\n\nWe continued making the robot in Turtle.\nLearnt how to compose functions.\n\nHomework:\n\nStill in the same file\, make a function for the right_leg and left_leg in the similar way you did for the other body parts\, and call the functions too. It should look like this:
URL:https://www.ayclogic.com/event/7-pm-intro-to-python-joshua-darin-sub/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260513T190000
DTEND;TZID=America/Los_Angeles:20260513T200000
DTSTAMP:20260720T091101
CREATED:20260514T030143Z
LAST-MODIFIED:20260514T030143Z
UID:33501-1778698800-1778702400@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\n\n\nFinished the Single Digit Classifier project.\n\nHomework:\nCome up with a final project if you haven’t already! \nChoosing what you want to classify — Can be anything in real life\, the only thing is you have to make sure the data exists on Kaggle. \nThe project has to be able to classify at least 5 different categories \nFor next week: \n\nSet up the labelling function\nVerify Dataloader works with .show_batch() (reference old code for how to do this\, it will depend on how you extract labels\, whether its via path or filename)\nRun training with a vision_learner.\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-27/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260511T173000
DTEND;TZID=America/Los_Angeles:20260511T183000
DTSTAMP:20260720T091101
CREATED:20260512T015317Z
LAST-MODIFIED:20260512T015317Z
UID:33473-1778520600-1778524200@www.ayclogic.com
SUMMARY:5:30 PM – Intro to Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe went over more Python Turtle applications.\nWe began to illustrate a robot using Python Turtle.\n\nHomework\n\nSketch your final project proposal.\n\nYou can draw on paper or draw on a tablet/Ipad.\nInclude color in your project proposal.\nI advise you to not make the illustration too complicated\, you will need to code this out in Python after all.\nBe creative\, you can draw anything you want!\n\n\nShow me your project proposal in-person in our next class or you can upload a photo of your project proposal in the Google Drive.\nHere are the instructions + the other students projects for inspiration: https://www.ayclogic.com/intro-to-python-final-project-criteria/\n\n\n\n\n\n\n\n\n\n\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/530-pm-intro-to-python-abigail-9/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260506T190000
DTEND;TZID=America/Los_Angeles:20260506T200000
DTSTAMP:20260720T091101
CREATED:20260507T030840Z
LAST-MODIFIED:20260507T030840Z
UID:33401-1778094000-1778097600@www.ayclogic.com
SUMMARY:7 PM – AI/ML – Darin
DESCRIPTION:Today’s Activities:\n\nContinued the Single Digit Classifier project.\n\nHomework:\nCome up with a final project! \nChoosing what you want to classify — Can be anything in real life\, the only thing is you have to make sure the data exists on Kaggle. \nThe project has to be able to classify at least 5 different categories \nFor next week: \n\nAfter picking the data for classification\, load the data into a dataloader. You don’t need a perfect labelling function yet.\nKeep a link to the dataset as well as your personal kaggle project. SET the project to public view then share the link to the project to me via email.\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-26/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260504T190000
DTEND;TZID=America/Los_Angeles:20260504T200000
DTSTAMP:20260720T091101
CREATED:20260505T000550Z
LAST-MODIFIED:20260505T000550Z
UID:33374-1777921200-1777924800@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\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-25/
CATEGORIES:AI/ML,Python Class
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260502T123000
DTEND;TZID=America/Los_Angeles:20260502T133000
DTSTAMP:20260720T091101
CREATED:20260502T203855Z
LAST-MODIFIED:20260502T203855Z
UID:33347-1777725000-1777728600@www.ayclogic.com
SUMMARY:12:30 PM – Intro to Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe went over turtle functions.\n\nHomework\n(Upload your homework into your Google Drive HW folder a day before the class starts) \n\nMake a new file called “May2_Turtle_Exercises_HW.py”\nDo these exercises\, but only the octagon problem as we already done the other functions: https://www.ayclogic.com/event/6-pm-intro-to-python-46/ \n\nFor the exercise\, put 3 parameters (x\, y\, pen_color) instead of just 1 parameter.\n\n\n\n# turn this code into a for loop solution\nt.forward(200)\nt.right(90)\nt.forward(100)\nt.right(90)\nt.forward(200)\nt.right(90)\nt.forward(100)
URL:https://www.ayclogic.com/event/1230-pm-intro-to-python-abigail-8/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260428T173000
DTEND;TZID=America/Los_Angeles:20260428T183000
DTSTAMP:20260720T091101
CREATED:20260429T014354Z
LAST-MODIFIED:20260429T014354Z
UID:33301-1777397400-1777401000@www.ayclogic.com
SUMMARY:5:30 PM – Intro to Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe went over Python Turtle basics.\n\nHomework\n\nCreate a diamond shape.\nIt must be filled with a color we haven’t used before.\nIt could be located anywhere on the screen.\n\n\n\n\n\n\n\n\n\n\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/530-pm-intro-to-python-abigail-8/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260427T190000
DTEND;TZID=America/Los_Angeles:20260427T200000
DTSTAMP:20260720T091101
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
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260425T123000
DTEND;TZID=America/Los_Angeles:20260425T133000
DTSTAMP:20260720T091101
CREATED:20260425T210138Z
LAST-MODIFIED:20260425T210138Z
UID:33272-1777120200-1777123800@www.ayclogic.com
SUMMARY:12:30 PM – Intro to Python – Abigail
DESCRIPTION:Today We\n\n\n\n\nWe went over the 2nd quiz.\n\nHomework\n\nCreate a function called age_classifier with one parameter called age\nThis function will RETURN a string depending on the age\n\nIf age is 5 or below = “Toddler”\nIf age is 18 or below = “Teen”\nIf age is above 18 = “Adult”\n\n\nCONTINUOUSLY ask the user what their age is\, then call the function using the user’s age to get a result.\nPrint out the result.\n\n\n\n\n\nIf you have any questions\, email me at abigail@ayclogic.com
URL:https://www.ayclogic.com/event/1230-pm-intro-to-python-abigail-7/
CATEGORIES:Python Class,Python Level 1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260422T190000
DTEND;TZID=America/Los_Angeles:20260422T200000
DTSTAMP:20260720T091101
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:20260420T190000
DTEND;TZID=America/Los_Angeles:20260420T200000
DTSTAMP:20260720T091101
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
END:VCALENDAR