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Showing posts with the label algorithms

Mark Rober's 14 minute long primer on machine learning

I'm a fan of former NASA engineer and current YouTuber/science comm pro  Mark Rober . He meets the sweet spot of containing YouTube content that is safe for kids but also engaging for adults. You may know him for creating obstacle courses for squirrels in his backyard and holding the world record for the tallest elephant toothpaste explosion .  Recently, I discovered that he made a stats-adjacent video  explaining machine learning by studying baseball signals and creating a way to de-code baseball signals . Anyway, if you touch on your topics in your classes, this is a great, quick explainer. It is well-edited, well-produced, and has captioning. You don't need to be a baseball fan to follow this example. 

"The Quest To Create A Better Spy-Catching Algorithm"

"(Algorithms) are used so heavily, they don't just predict the future, they are the future." -Cathy O'Neil ^This quote from this NPR story made me punch the air in my little Subaru after dropping my kid off to school. What a great sentence. There are many great one-liners in this little five-minute review of algorithms. This NPR story by Dina Temple-Raston is a great primer for All The Ethical Issues Related To Algorithms, accessible to non- or novice-statisticians. It clocks in at just under five minutes, perfect as a discussion prompt or quick introduction to the topic. How to use in class: They talk about regression without ever saying "regression": "Algorithms use past patterns of success to predict the future." So, regression, right? Fancy regression, but that one line can take this fancy talk of algorithms and make it more applicable to your students. Sometimes, I feel like I'm just waving my hands when I try to explain thi...