Your personal Machine Learning Starter Kit

Machine Learning Starter Kit — 172-Page Practical Handbook (€19)
A Practical Handbook · €19

The Machine Learning Starter Kit — from your first line of Python to deployed models

A 172-page machine learning starter kit with 26 chapters. Every code listing was actually executed — the outputs on the page are the real ones.

Get the Starter Kit — €19 → Instant download · PDF · Yours forever
Machine Learning Starter Kit book cover — a practical handbook from your first line of Python to deployed models
⚙️

Code that ran

Every listing was executed before printing. What you see is what Python returned.

📚

26 chapters

From Python basics through algorithms, evaluation, and deployment — in one arc.

🔎

57-term glossary

Every ML term you’ll hit in docs and interviews, defined in plain language.

No cherry-picking

We print the real output. Even when it surprises us.

Most ML books show idealized results. In the Starter Kit, every listing was executed and its output captured verbatim — including the chapter where a simple baseline beat the fancy model.

That’s not a bug. Learning why it happened is the lesson.

# Chapter 14 — comparing models on the same split
for name, model in models.items():
    model.fit(X_train, y_train)
    acc = model.score(X_test, y_test)
    print(f"{name:<22} {acc:.3f}")

LogisticRegression     0.891
RandomForest           0.874
GradientBoosting       0.882

# Yes — the simplest model won. Chapter 14
# explains exactly why.

What’s inside the Machine Learning Starter Kit

26 chapters · 4 parts · one continuous build from zero to deployed

PART I · CH 0–6

Foundations

Python, environments, NumPy, Pandas, and the math you actually need.

PART II · CH 7–14

Core Algorithms

Regression, classification, trees, forests, SVMs — built and compared.

PART III · CH 15–20

Evaluation & Tuning

Metrics, validation, feature engineering, and honest model comparison.

PART IV · CH 21–25

Ship It

End-to-end projects, deployment, and turning work into a portfolio.

00 Setting up your machine
05 The math that matters
08 Your first classifier
12 Random forests, demystified
16 Metrics beyond accuracy
19 Feature engineering in practice
22 An end-to-end project, start to finish
25 Deploying your first model

Want to go deeper on any topic? The Kit pairs well with our curated machine learning books, ML online courses, free datasets for practice, and ready-to-use code snippets.

€19

Skip the tutorial maze. Start executing.

One PDF, 172 pages, every line of code tested. Buy once, keep forever, learn at your own pace.

Get the ML Starter Kit → Secure checkout via Gumroad · Instant PDF delivery

Who is the Machine Learning Starter Kit for?

The Kit is written for people who learn by running code, not just reading about it. It’s a perfect fit if you are:

  1. A roadmap follower: you’re working through the free 90-Day Roadmap and want the code companion.
  2. A hands-on learner: you understand things when you can run them, break them, and fix them.
  3. A career changer: you need working projects, not just theory, to show employers.
  4. A busy self-learner: you’d rather pay €19 than spend weeks assembling scattered tutorials.

Frequently Asked Questions

How is this different from the free 90-Day Roadmap?

The roadmap is a complete, free strategy: it tells you what to learn each day and links you to resources. The Starter Kit is the execution shortcut: 172 pages of explained, tested code so you don’t have to assemble it yourself. You can absolutely succeed with just the roadmap — the Kit saves you time.

What format is the book?

A downloadable PDF, delivered instantly after purchase through Gumroad. Read it on any device; it’s yours forever, including future updates to this edition.

Do I need prior experience?

No. Chapter 0 starts with setting up Python from scratch. If you already code, the early chapters go quickly and the algorithm and evaluation chapters are where you’ll spend your time. If you’d like extra Python practice alongside the book, check our Python courses and Python books pages.

Is the code really executed?

Yes — every listing was run before printing, and the outputs on the page are captured verbatim from those runs. When a result was surprising, we kept it and explained it rather than swapping in a prettier number.

What tools do I need?

A laptop that runs a browser. Everything in the book uses free tools: Python, Jupyter, Google Colab, and scikit-learn. No paid software.

What comes after the Starter Kit?

Once you’ve finished the book, keep building: work through our free tutorials, practice on real datasets, and specialize with our curated statistics courses and AI books.

Can I get a refund?

If the Kit isn’t what you expected, reply to your purchase email within 14 days and we’ll refund you. No forms, no friction.

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