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9 𝐃𝐢𝐬𝐭𝐚𝐧𝐜𝐞 𝐌𝐞𝐚𝐬𝐮𝐫𝐞𝐬 𝐢𝐧 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞
Many #machinelearning algorithms, whether supervised or unsupervised, make use of distance measures.
Take k-NN for example, a technique often used for supervised learning. As a default, it often uses euclidean distance.
By itself, a great distance measure.
Knowing when to use which distance measure can help you go from a poor classifier to an accurate model.
Study: https://towardsdatascience.com/9-distance-measures-in-data-science-918109d069fa
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Pick up a good accounting and finance book, covers most of the "hard" stuff you'll actually have to study for in b-school. As an engineering major, the "rigor" of an MBA is kind of a joke. Don't sweat it.
Maybe some basic finance/accounting. It's really easy coming from an engineering background. They'll act like it's hard. Just nod your head.
B school is super easy don't bother with the pre study
Thank-you.
What the heck is a pre-MBA course? As an MBA student I've never heard of this.