Alpha's Manifesto

A black and white figure's thought-hive

Correlation ≠ causation

But causation ⇒ correlation

Correlation vs causation

In my earlier post I explained how certain type of machine learning models, specifically neural networks, find the correlations between two sets of values. For predictive models, we feed correlated variables to train our models. However, sometimes, we don’t know if or how variables correlate, and part of the machine learning intelligence is to actually find that out.

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Neural Networks can learn anything

A simple explanation on the basis of neural network learning

Neural Networks

This is a question I’ve been recently asked, and I think it’s interesting enough to share about. A few people asked me how is it that machines can learn, and specifically, how is it that neural networks can learn to understand data that may be really complex. The goal of this article is not to give an in-depth explanation, but rather one that can be easily understood.

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