Why ML is a metaphor for life
The article draws parallels between machine learning concepts and everyday life experiences. It emphasizes how individuals constantly solve optimization problems, similar to training neural networks to minimize loss functions. By recognizing local minima in life, people can seek additional information to improve their situations.
- ▪Machine learning involves training neural networks to minimize a loss function for accurate predictions.
- ▪In life, individuals face optimization problems, such as choosing efficient routes or managing distractions.
- ▪Local minima in life represent challenging situations where progress feels stalled, similar to points in machine learning where further minimization is difficult.
Opening excerpt (first ~120 words) tap to expand
Why Machine Learning Is A Metaphor For Life Seriously. Hear me out on this. The more I learn about ML, the more I see the number of similarities there are between life and machine learning concepts. Specifically, let’s think about neural networks. Let's think of a neural net that has a bunch of input nodes and one output node. The input features are encapsulated in some input vector x, and we’d like to come up with a single scalar prediction ŷ. The way you compute ŷ is by passing x through a series of linear operations with weight matrices mixed in with a couple activation functions. Simple enough. But in order to get accurate ŷ predictions, we need to first train our network. When training neural networks, the goal is to be able to minimize a loss function. That’s the name of the game.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Github.
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