How Machines Think
How Machines Think
A Guided Journey to the Heart of AI
A narrative journey following a medical team implementing AI at Minermont Hospital. We start with solid foundations (so nothing is “magic”) and move step by step to the heart of language models: why an LLM can understand and generate text.
🚪 Open the AI Black Box
Artificial intelligence is no longer a distant promise. This book doesn’t just open the black box: it guides you inside, connecting intuition, math, and real cases so the “miracle” becomes a mechanism.
📚 Unique Narrative
Learn AI through the story of Minermont Hospital, where science comes to life in real situations and crucial medical decisions.
Story + Technical🔍 Explainability
Understand not just WHAT algorithms do, but WHY they work. Every concept explained from mathematical foundations to practical application.
Transparency💻 Interactive Components
Widgets and visualizations that let you experiment with algorithms in real-time, adjust parameters and see results immediately.
Active Learning
💡 Why this approach works
By combining a real medical narrative with rigorous technical explanations, you don't just memorize algorithms, you deeply understand how and why they work. Each concept is presented in context, facilitating retention and application to real problems.
What you'll discover on this journey
- Understand how AI works from scratch, without needing to be a mathematician
- See how machines learn from real examples, like at Minermont Hospital
- Discover how AI helps diagnose diseases and predict medical outcomes
- Learn why it's important to test and validate AI models
- Explore intuitive methods of automated decision-making
- Introduction to neural networks, the "brain" of modern AI
- Understand how chatbots and assistants understand human language
- Reflect on the ethical challenges of using AI in medicine and other critical fields
📍 Your Learning Path
From foundations to the most advanced models, you'll follow a structured and progressive path
Solid Foundations
Start with linear regression and classification. No "magic" - you'll understand every mathematical step.
Intuitive Algorithms
Explore decision trees and k-neighbors. Methods that "make sense" and work.
Neural Networks
Discover how neural networks work from perceptron to backpropagation.
The Heart of Modern AI
Reach LLMs and transformers - understand why ChatGPT can talk to you.
Book Contents
9 chapters that take you from basic concepts to the most advanced language models
The Beginnings of AI
History and evolution of artificial intelligence, from early concepts to the modern era.
Linear Regression
Foundations of supervised learning: how machines find relationships in data.
Classification
Logistic regression and classification methods for binary and multiclass decisions.
Trees and Neighbors
Decision trees and K-nearest neighbors: intuitive and powerful algorithms.
Clustering
K-means and discovering hidden patterns in unlabeled data.
Neural Networks
Perceptrons, backpropagation and the foundations of deep learning.
Language Models
LLMs, transformers and natural language processing revolutionizing AI.
From Tokens to Thought
Post‑training, RLHF, and reasoning LLMs: from “next token” to responsible deployment.
Real‑World Cases
Verifiable deployments and methodology: medicine, education, mathematics, and software.
Key Themes
Explainability
Understanding WHY an AI makes a decision is as important as the decision itself. Transparency in every algorithm.
Responsibility
Who is responsible when AI makes a mistake? Balancing automation with human judgment and medical oversight.
Technical Rigor
Solid mathematical foundations of supervised learning, presented with real human context and practical applications.
Real Implementation
The challenges of integrating AI into existing workflows, model validation and user acceptance.
Frequently Asked Questions
Do I need prior knowledge of math or programming?
No. The book is designed to be accessible without specialized prior knowledge. Mathematical concepts are explained from scratch with clear intuitions before formalizing.
What makes this book unique compared to other AI resources?
It combines an engaging narrative (the Minermont Hospital story) with technical rigor. Each concept is presented in context, with the "why" as well as the "how", and reinforced with interactive components.
Do the interactive components work on mobile devices?
Yes, all widgets and visualizations are optimized to work on mobile devices and tablets, although the full experience is best appreciated on larger screens.
How do I progress through the trilogy after this book?
This is Book 1 which establishes the foundations. Book 2 ("Eyes and Ears") explores vision and audio, and Book 3 ("Learning Without a Teacher") covers unsupervised and reinforcement learning.
Where can I buy the book?
The book is available on Amazon.com.
Start Your Journey
Explore the complete book now and discover how machines think