Graphic Design Portfolio

Passion Projects

This page serves as an outlet for me to share new side projects and random little (and big) experiences that I’m proud of.

"AI For Everyone" Presentation

I took advantage of some downtime to take a class on AI, through Coursera. The class was called “AI For Everyone” taught by Andrew Ng of DeepLearning.ai

As a highly visual person who has never felt comfy putting on a “developer” hat, I’ve felt like AI isn’t really in my wheelhouse, so to speak. I use tools like Dall-E, and ChatGPT in my work regularly, but never felt like I could step into the creator process of AI tools. I’m happy to report, though, that this class helped me to reframe that way of thinking.

The class taught me the basics of AI, the hot buzzwords, where things are today and where they’re going. In addition, though, Andrew walked me through the process of creating AI, and the general idea of how these types of projects and teams function. In my excitement to help steward this type of thinking within my own team, I was encouraged to share my takeaways of the course with my colleagues.

I was told “no need to make a presentation or anything”… so naturally I absolutely made a presentation. And after the first smiley face was added, things really took off. So alas, here we are with all these cuties.

Almost all of the AI progress that we’re seeing today is Artificial Narrow Intelligence (ANI), whereas Artificial General Intelligence (AGI) is the eventual goal.

Of AI, the biggest subset is ML,  and of ML, the biggest subset is Deep Learning.

Artificial Intelligence (AI) - Computers doing stuff humans do

Machine Learning - Teaching software to use an input/data to get an output (A → B)

Deep Learning - Software with a big artificial neural network / handles more complex equations (A+A+A+A+A → B)

Machine Learning (ML) is the process of teaching a computer to learn pattern from data, and then apply those patterns to make predictions on new data.

So A —> B.

RESOURCES

If you’re interested, I absolutely recommend taking the class, and digging into all of the resources that are out there! Here are a few that I’d recommend:

The five step AI transformation playbook

  1. Execute pilot projects to gain momentum 

  2. Build an in-house AI team

  3. Provide broad AI training

  4. Develop an AI strategy

  5. Develop internal and external comms 

TensorFlow’s Women in Machine Learning Symposium

Take the Coursera Class, AI for Everyone

Beyond that, read books & blogs, watch demos, talk to experts, etc.!

Megan Althaus