#The cheat sheet bias how to#

Decisions inform our mental models of the world. This isn’t getting easier, so we try to remember the important bits. Need to act fast lest we lose our chance, so we jump to conclusions. It’s used to predict values within a continuous range, (e.g.

Lack of meaning is confusing, so we fill in the gaps. ML Cheatsheet Documentation 1.1Introduction Linear Regression is a supervised machine learning algorithm where the predicted output is continuous and has a constant slope. Information overload sucks, so we aggressively filter. Ill denote vectors with a little arrow on the top. Please note: I changed the notation very slighty. Dont gamble with your companys investigation process. start by remembering these four giant problems our brains have evolved to deal with over the last few million years.: This cheatsheet wants to provide an overview of the concepts and the used formulas and definitions of the »Machine Learning« online course at coursera. This free cheat sheet examines five tactics that investigators can use to better understand their own biases in order to help them conduct fair investigations.

but make sure they don’t begin discussing them out loud it can bias or rush the others. I have moved the content of this blog to the DDD-crew GitHub page, were it will be updated by the community.

#The cheat sheet bias how to#

a simpler, clearer organizing structure to hang these biases off of.īiases help us address: Information overload, lack of meaning, the need to act fast, and how to know what needs to be remembered for later. In this EventStorming cheat sheet post, I will describe these basic requirements in a cheat sheet. groups 175 biases into vague categories (decision-making biases, social biases, memory errors, etc) that don’t really feel mutually exclusive to me, and then lists them alphabetically.