Assignments 2020-2021

Assignment 1 (8/31/20):

If you haven’t read the Club Information Post, please do so first. You should do the assignment in order of:

1. PowerPoint presentation

2. Additional Links

3. Fill out virtual attendance form

Since this time is just an introduction, we have not made a coding assignment. Feel free to email us (wwhs.aiexploration@gmail.com), comment in the stream, or comment on this assignment if you have any questions.

Assignment 2 (9/13/20):

Remember, as of now, we don’t have live “meetings”. Please fill out the attached Virtual Attendance form so we can count you as one of our active members.

The assignment for Meeting 2 is:

1. PowerPoint (it should take about 20 minutes to go through)

2. Optional Colab Assignment (really simple - you don’t have to turn anything in). Once you open the file, click the “open with Google Colaboratory button”.

Thank you if you made a suggestion in the form (like object detection or virtual assistants)! We will try to incorporate it into our curriculum this year

If you had a specific question, we addressed it in the FAQs document attached (or the FAQs 9/7 document below in the stream).

Assignment 3 (9/27/20):

Here is the material for Meeting 3:

1. AI and Finance Presentation (as requested by some of our members. It should take about 20 minutes to go through)

2. Colab Python Tutorial (useful only if you are unfamiliar with Python)

3. Advanced Colab Tutorial (completely optional, if you completed the previous Colab Tutorial, this is an extension).

Some reminders

1. Go through this material asynchronously. There are no live meetings yet.

2. You do not need to turn anything in except the attached virtual attendance form.

3. Once you open a Colab file, click the “open with Google Colaboratory button”.

As we start to code more, you will probably encounter bugs and errors. Google and sites like Stack Overflow are really helpful to solve them. But always feel free to email us (wwhs.aiexploration@gmail.com) with questions or comment in the Classroom stream.

Assignment 4 (10/12/20):

Here is the material for Asynchronous Meeting 4:

1. Understanding Gradient Descent - This is a fundamental concept in AI showing how machines “learn” by themselves. It should take about 20 minutes to go through.

2. Optional Linear Regression Colab Tutorial (this includes a “competition” aspect, remember to click “Open with Colaboratory” after opening the file)

We hope to make an announcement regarding live meetings soon. Also, we hope to do one-on-one tutorials to help you with your code soon. Stay tuned!

Meeting 5 (11/9/20):

Stanford University machine learning student and researcher Ricky Grannis-Vu is joining our club’s first synchronous meeting to teach a lesson on Neural Networks and talk about some AI related opportunities offered by his organization.

Please mark your calendars for November 9th at 4PM. The meeting is approximately an hour long and will be hosted by our club sponsor Mrs. Jennifer Howitt and the officer team.

We will post some additional Colab notebooks (like stock price prediction or a neural network introduction) on the weekend of 11/15 for extra practice. Remember, if you have any questions, please sign up for tutorials through the form on the Google Classroom.

Meeting 6 (11/30/20)

Welcome back from the break!

The material for Async Meeting 6 is:

1. Presentation on Neural Networks and other machine learning concepts

2. Presentation on Chatbots (as requested by some of our members)

3. Colab notebook: Neural network to predict stock prices (this has an optional “competition” aspect, the data is attached to this assignment)

4. Colab notebook: A neural network from scratch (there’s nothing to “run” here, but if you know Python well, we made this so that you can associate lines of code with concepts in the PowerPoint)

Remember to fill out the attendance form! And only do as much as you can handle.

The material is pretty complex, so if you need it, we are also attaching a one-on-one tutorial signup form to this assignment. Please indicate days and times you are available, and we will contact you and set up a Zoom meeting.

Thanks!

AI Club

Announcement (1/12/21)

Welcome back from the break! Science Fair is right around the corner and AI-related projects have become really successful in recent years. If you are doing an AI/machine learning based project or if you want to start one, we are happy to help you with resources and guidance.

If you would like to sign up for our Science fair mentorship, please fill out the form below and we will contact you.

https://docs.google.com/forms/d/e/1FAIpQLScr3s1yeAaDWlD3fbyf0LAmBUGJVZLum8bgaFZw0VMNGOl82A/viewform

Meeting 7 (1/20/21)

This is the material for the first asynchronous meeting of the semester:

1. A quick PowerPoint refreshing machine learning concepts after the break and walking you through an example

2. An optional Colab notebook coding a neural network to recognize pieces of clothing

Our plan is to dive deep into neural networks this semester, learning everything from generating text to creating AI “art”.

Meeting 8 (2/6/21)

The material for this time is a short PowerPoint (it should take about 20 minutes) covering the use of AI in Social Media. We highly recommend you go through the entire presentation - it will help you understand how companies like Twitter “recommend” content and the implications of their algorithms. The answer key for last time's Fashion MNIST Colab Notebook is also attached.

Meeting 9 (3/9/21)

At the synchronous meeting today, we covered Computer Vision and its applications in healthcare. See below for the slideshow as well as a Colab notebook showing a Convolutional Neural Network coded in Python.

Meeting 10 (4/13)

The material for this time's asynchronous meeting is below:

1. Natural Language Processing Presentation

2. AI Club "Project" Section 1(see Colab notebook for details)