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1.2 Mathematics for AI

Beginner · 8 articles · MODULE 1: FOUNDATIONS

Probability & Statistics Foundations

Tutorial · Beginner · 24 min

This is the refresher everything else stands on. A probability is a proportion between 0 and 1, and a risk is exactly that — events divided by everyone.

Linear algebraProbability

Includes Colab notebook

By: Anacodic Team

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Logarithms, Exponents & the Log Scale

Tutorial · Beginner · 22 min

An exponent builds a number up by repeated multiplication (10^3 = 1000); a logarithm is its exact inverse — it asks "what power gives me this number?" (log10(1000) =…

Linear algebraProbability

Includes Colab notebook

By: Anacodic Team

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Weighted Averages & Aggregation

Tutorial · Beginner · 17 min

A weighted average lets some numbers "count more" than others.

Linear algebraProbability

By: Anacodic Team

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Fair Aggregation: Balancing Utility and Fairness

Tutorial · Beginner · 16 min

When a single choice must serve a whole group, you combine each person's satisfaction into one score and pick the highest-scoring option.

Linear algebraProbability

By: Anacodic Team

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Measuring Fairness: Jain, Gini, Min, and Envy

Tutorial · Beginner · 15 min

Once you split something among people — bandwidth, budget, or satisfaction with a shared choice — you need a number for how fairly it was split.

Linear algebraProbability

By: Anacodic Team

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Shapley Values: Fairly Attributing Credit to Features and Agents

Tutorial · Beginner · 15 min

When several parts cooperate to produce one result, the Shapley value fairly attributes credit by averaging each part's marginal contribution over every order it could join.

Linear algebraProbability

By: Anacodic Team

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Information Theory

Tutorial · Beginner · 20 min

Entropy, surprisal and perplexity explain what a language model's loss number means. Confidence and correctness are different axes.

Information theoryProbability

By: Anacodic Team

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Linear Algebra

Tutorial · Beginner · 22 min

Almost every number a model produces comes out of one operation: matrix multiplication. Shapes are the debugging, and cost is n times k times m.

Linear algebraVectors

By: Anacodic Team

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