It’s Christmas time… — Oh wait, it isn’t! But Santa Claus is coming back to share some insights with you from our AI readiness program. In the context of our transformation journey we had an initiative taking place in December with the goal of fostering AI education and inspiration inside Scout24: An AI advent calendar.
What was the AI advent calendar exactly?
Advent calendars are a German tradition for children — and more and more also for grownups. (– oh yes, companies are smart and totally jump into it by selling whisky advent calendars, cosmetics advent calendars and whatever-you-can-think-of-advent-calendars lately. I actually got a green tea advent calendar I am still figuring out which ones I want to re-order right away! The Thai Lemon one is totally in my shopping bag! But I’m getting off track :D…) How does the concept work? — Between December 1st and 24th (Christmas eve) advent calendar owners at Scout24 were allowed to open a door of the advent calendar and remove the chocolate/whisky/tea/whatever and enjoy.
We used the advent calendar tradition and created a journey through all working days in advent with a daily dose of information on AI and ML. We wanted to feed it with digestible pieces for total AI beginners as well as more advanced employees. We also wanted to draw a concise story.
We wanted to create a read thread throughout the month. We started with the reason why and definition of ML/AI, continued with the what it exactly is and does and then dived into good practices about how to do it — also from a PM and UX perspective. We additionally weaved internal and external examples in wherever it fitted.
This was the content:
Day 1: What do a hammer and nails have to do with Machine Learning (ML)?
Why do it? What’s in for you/us or why AI and Machine Learning are crucial for businesses. https://medium.com/@yaelg/product-manager-guide-part-1-what-machine-learning-can-do-for-your-business-and-how-to-9f7eb7dced05 Thanks, Yael Gavish!
Day 2: 10 examples of what companies actually do with ML
Day 3: What does a cat has to do with Deep Learning* — OR What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning https://thenextweb.com/syndication/2018/11/21/the-difference-between-ai-and-machine-learning-explained/amp/
Day 4: How can IKEA furniture help understand the idea of Machine Learning Models? What’s the Difference Between Supervised, Unsupervised, Semi-Supervised and Reinforcement Learning?
Day 5: Regression & Classification and what a Koala has to do with this
https://medium.com/scout24-engineering/introduction-to-machine-learning-pt-1-a190a8645298 Thanks, @ Stephen Wilson!
(In a training dataset of animal images, that would mean each photo was pre-labeled as cat, koala or turtle. The algorithm is then evaluated by how accurately it can correctly classify new images of other koalas and turtles.)
Day 6: UNsupervised learning and the parallel to unthoughtful IKEA shopping:
Imagine you drive to your IKEA to grab a random box, toss away the manual at home and see where you are going.
So, what would you do?
Right! You would see what you can make out of the different pieces.
And the result could be very different! — Out of a PAX box you might create an (instable) bank or a shelf without doors or a couch table (medium stable … ;) or something completely different!)
Day 7: Cool, visual introduction to some machine learning concepts taking a housing example — Oh I LOVE that one: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
Day 8: What is Reinforcement Learning (RL)? https://medium.freecodecamp.org/a-brief-introduction-to-reinforcement-learning-7799af5840db
Day 9: How to better explain neuronal networks by letting people try out themselves & have fun doodling: https://quickdraw.withgoogle.com/?locale=en_US
Day 10: GANs explained by SpongeBob (Yes, you heard it right! :D) https://medium.com/@awjuliani/generative-adversarial-networks-explained-with-a-classic-spongebob-squarepants-episode-54deab2fce39 Thanks, Arthur Juliani!
Day 11: I had heard several times over the first 2 weeks of the advent calendar that people who were not yet so deep into ML and Data Science struggled to decide whether ML/AI should be applied for solving a specific problem. Sounds familiar? The following awesome blog post of Cassie Kozykov helps with this challenge! https://hackernoon.com/imagine-a-drunk-island-advice-for-finding-ai-use-cases-8d47495d4c3f
Thanks, Cassie Kozyrkov!
Day 12: Why you need to define success or “The right time to think about your goals is at the very beginning, while your project is still a puppy!” — Takeaway: It’s the same as in every other project. If you don’t define success it’s hard to meet it! https://hackernoon.com/the-first-step-in-ai-might-surprise-you-cbd17a35708a
Day 13: The role of UX and Explainability in ML: https://medium.com/@yaelg/product-manager-guide-part-5-machine-learning-is-very-much-a-user-experience-ux-problem-82ad312678ae
Day 14: Kind of a Checklist for Machine Learning projects — it’s a good start for thoughts and planning https://hackernoon.com/ai-reality-checklist-be34e2fdab9
Day 15: Moral & Ethics– never forget!! “Test” your own views with the http://moralmachine.mit.edu/!
We started our AI Readiness Program @Scout24 in 2018 to make the company truly AI ready. As AI Evangelist my mission is to bring the right ideas to meaningful life.
It means also educating and inspiring the company as well as finding the right structures and processes with the teams in order to run smooth and fun AI projects.
Reach out to me if you want to get to know more!
*Cats, cats everywhere! If you were curious, here’s the solution: https://www.theverge.com/2012/6/26/3117956/google-x-object