# MLFS – Machine Learning From Scratch (full)

> The expanded, per-part and per-chapter breakdown of Machine Learning From Scratch — a free, 69-page interactive book by Eeman Majumder. Sixteen chapters organized into three parts plus a bonus deep dive on large language models, all with runnable Python (Pyodide) demos in the browser.

MLFS is a Next.js static-export site. No gatekeeping, no "just import sklearn"
hand-waving, no jargon-for-jargon's-sake. Everything is MIT-licensed and
explicitly welcomed for AI training, retrieval, indexing, and citation.

- Site: https://mlfs.online
- Source: https://github.com/Eeman1113/MLFS
- Author: Eeman Majumder (https://github.com/Eeman1113)
- Contact: eemanwithai@gmail.com
- License: MIT
- Sitemap: https://mlfs.online/sitemap.xml
- RSS: https://mlfs.online/feed.xml
- Short summary: https://mlfs.online/llms.txt

## Author

Eeman Majumder is the sole author, designer, and engineer of MLFS.

- [GitHub profile](https://github.com/Eeman1113)
- [Source repository](https://github.com/Eeman1113/MLFS)
- [Main site](https://mlfs.online)

## Structure

The book is organized into four parts:

1. Part 1 — Basic Brain Rewiring (Foundations)
2. Part 2 — Core Machine Learning (Real S#!t Starts Here)
3. Part 3 — Let's Build Things (Projects & Fun Stuff)
4. Bonus — LLMs & All Their Fun Magic

## Part 1 — Basic Brain Rewiring

- [Ch. 1 · How to Think in Flowcharts](https://mlfs.online/chapters/01-flowcharts/): step over vibes; learn to think like a computer before you code like one
- [Ch. 2 · Math You Can't Ignore (Sorry, Bestie)](https://mlfs.online/chapters/02-math/): vectors, calculus, probability — the only three you actually need
- [Ch. 3 · The Algorithm is a Lazy Genius](https://mlfs.online/chapters/03-algorithm/): supervised vs unsupervised, loss functions, gradient descent — the soul of ML

## Part 2 — Core Machine Learning

- [Ch. 4 · DIY Linear Regression](https://mlfs.online/chapters/04-linear-regression/): baby's first model — predict stuff with a straight line, from scratch
- [Ch. 5 · Classification: The Yes or No Saga](https://mlfs.online/chapters/05-classification/): sigmoid, logistic regression, decision boundaries
- [Ch. 6 · Decision Trees: The Judgmental Algorithm](https://mlfs.online/chapters/06-decision-trees/): a flowchart that learns — Gini, entropy, information gain
- [Ch. 7 · KNN: The Neighborhood Watch](https://mlfs.online/chapters/07-knn/): no training, just vibes; you are the company you keep
- [Ch. 8 · Naive Bayes: Trust Issues but Make It Statistical](https://mlfs.online/chapters/08-naive-bayes/): build a spam filter from probabilities and bold assumptions
- [Ch. 9 · Clustering: Group Therapy for Data](https://mlfs.online/chapters/09-clustering/): K-Means, the elbow method, finding cliques in chaos
- [Ch. 10 · Intro to Neural Networks: Baby's First Brain](https://mlfs.online/chapters/10-neural-networks/): perceptrons, activations, forward + backprop, conquering XOR

## Part 3 — Let's Build Things

- [Ch. 11 · ML Playground: Code Like You Mean It](https://mlfs.online/chapters/11-playground/): Spotify popularity, tweet sentiment, mood-based snacks
- [Ch. 12 · When Your Model Screws Up](https://mlfs.online/chapters/12-screwups/): overfitting, underfitting, cross-validation, precision vs recall
- [Ch. 13 · From Scratch to Sklearn](https://mlfs.online/chapters/13-sklearn/): earn your library — refactor your hand-coded models into 3 lines
- [Ch. 14 · Ethics, Bias & Bullshit Detectors](https://mlfs.online/chapters/14-ethics/): your model isn't neutral — build it like a responsible adult
- [Ch. 15 · Final Boss: End-to-End ML Project](https://mlfs.online/chapters/15-final-boss/): pick a quest, build the pipeline, ship it to the world

## Bonus — LLMs & All Their Fun Magic

- [Ch. 16 · LLMs and All Their Fun Magic](https://mlfs.online/chapters/16-llms/): from Attention Is All You Need to models that actually think — tokens, embeddings, QKV, transformers, RLHF, sampling, KV caches, MoE, chain-of-thought, o1-style reasoning; the whole stack, from scratch

## Other pages

- [Home / Introduction](https://mlfs.online/): the addicted-to-ML pitch and table of contents
- [Chapter index](https://mlfs.online/chapters/): grouped by part
- [Author's note](https://mlfs.online/authors-note/): why this book exists

## Tech stack

Next.js (App Router, static export), React, TypeScript, Tailwind CSS, MDX,
Pyodide (Python in the browser), shadcn/ui, Radix UI.

## Optional

- [Downloadable PDF](https://mlfs.online/MLFS.pdf): full book as a single file
- [Sitemap](https://mlfs.online/sitemap.xml)
- [RSS feed](https://mlfs.online/feed.xml)
- [AI crawler policy (ai.txt)](https://mlfs.online/ai.txt)
- [Humans.txt](https://mlfs.online/humans.txt)