AI for Dummies (Series) — Carlos Rodrigues

Predicting Diabetes with Machine Learning – a brief introduction to Tensorflow: AI for Dummies #1

Part #1

11 min read • 2025-11-07

Predicting Diabetes with Machine Learning – a brief introduction to Tensorflow: AI for Dummies #1

Everybody uses AI for almost everything these days. From helping shaping ideas to the recommendation systems that tells us which movie to watch next, it’s Continue readingPredicting Diabetes with Machine Learning – a brief introduction to Tensorflow: AI for Dummies #1

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Handling Categorical Data with One-Hot Encoding: AI for Dummies #2

Part #2

8 min read • 2026-06-11

Handling Categorical Data with One-Hot Encoding: AI for Dummies #2

If you’ve been following along with this series, you’ll know that in the first post we built a simple ML model to predict diabetes. We kept things… Continue readingHandling Categorical Data with One-Hot Encoding: AI for Dummies #2

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Part #3

6 min read • 2026-06-19

Feature Scaling: AI for Dummies #3

One of the things that may be bothering you if you followed #1 and #2 is the fact that we never talked about what happens… Continue readingFeature Scaling: AI for Dummies #3

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Understanding backpropagation: AI for Dummies #4

Part #4

3 min read • 2026-07-26

Understanding backpropagation: AI for Dummies #4

If you have spent any time in the machine learning space, you have inevitably scratched your head around the concept of backpropagation. It is the… Continue readingUnderstanding backpropagation: AI for Dummies #4

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Part #5

6 min read • 2026-08-06

Target Encoding: AI for Dummies #5

At the end of our One Hot encoding article, we left a small elephant in the room: what happens when your categorical column has 50… Continue readingTarget Encoding: AI for Dummies #5

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GraphRAG – how agents can leverage structured knowledge and stay on track: #AI for dummies #6

Part #6

15 min read • 2026-08-08

GraphRAG – how agents can leverage structured knowledge and stay on track: #AI for dummies #6

This article compares standard vector RAG with GraphRAG, explaining when global synthesis and multi-hop reasoning justify higher ingestion cost and latency. It then builds a PostgreSQL proof of concept using pgvector and Apache AGE with Docker and a Python retrieval pipeline.

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Why deterministic tests are not enough in the world of AI: An Introduction to AI Evals – AI for Dummies #7

Part #7

7 min read • 2026-08-12

Why deterministic tests are not enough in the world of AI: An Introduction to AI Evals – AI for Dummies #7

If you are a software engineer stepping into the world of LLMs and AI engineering, you have likely encountered this or a very similar frustrating… Continue readingWhy deterministic tests are not enough in the world of AI: An Introduction to AI Evals – AI for Dummies #7

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Improving evals by teaching an LLM to Grade Another LLM – AI for Dummies #8

Part #8

29 min read • 2026-09-02

Improving evals by teaching an LLM to Grade Another LLM – AI for Dummies #8

At the end of our first article on the AI Evals mini series we left a small elephant in the room: fuzzy matching works great… Continue readingImproving evals by teaching an LLM to Grade Another LLM – AI for Dummies #8

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Catching AI Regressions in CI/CD Before Your Users Notice – AI for Dummies #9

Part #9

19 min read • 2026-09-22

Catching AI Regressions in CI/CD Before Your Users Notice – AI for Dummies #9

With new AI frameworks, model updates, and prompt engineering techniques dropping (almost) every single week, we get this constant feeling of being behind. (I do,… Continue readingCatching AI Regressions in CI/CD Before Your Users Notice – AI for Dummies #9

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AI for Dummies

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