LLMs from Scratch vs 
Hands-On Machine Learning
LLMs from Scratch vs Hands-On Machine Learning compared for 2026 — features, license, ease of use, performance and which one to choose. Build a GPT from nothing, line by line vs The notebooks of the best-selling ML book.
Updated regularly · curated by OpenSourceAI.tech
LLMs from Scratch vs Hands-On Machine Learning at a glance
| Spec | LLMs from Scratch | Hands-On Machine Learning |
|---|---|---|
| Category | Learn AI & machine learning | Learn AI & machine learning |
| Type | Book + code | Book notebooks |
| License | Apache-2.0 | Apache-2.0 |
| Runs locally | Yes | Yes |
| Primary language | Python | Jupyter |
| Ease of use | Intermediate | Intermediate |
| Best for | genuinely understanding how an LLM works | the classic path from scikit-learn to deep learning |
| GitHub stars | 99k | — |
How LLMs from Scratch and Hands-On Machine Learning score
| Criterion | LLMs from Scratch | Hands-On Machine Learning |
|---|---|---|
| Popularity | 4.5 | n/a |
| Maintenance | 5.0 | n/a |
| Ease of use | 3.5 | 3.5 |
| Privacy | 5.0 | 5.0 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
LLMs from Scratch
Sebastian Raschka's companion repository to "Build a Large Language Model (From Scratch)": you implement attention, a transformer, pretraining and fine-tuning yourself, in plain PyTorch.
- You build every component yourself — no black boxes
- Runs on a laptop, no cluster needed
- The clearest explanation of attention anywhere
Hands-On Machine Learning
Aurélien Géron's companion notebooks: scikit-learn for classical ML, then Keras and TensorFlow for deep learning — the reference practical ML book.
- The most widely used practical ML book
- Every chapter is a runnable notebook
- Covers classical ML properly, not just neural nets
Key differences
LLMs from Scratch is book + code, while Hands-On Machine Learning is book notebooks. In short, LLMs from Scratch fits genuinely understanding how an LLM works, and Hands-On Machine Learning fits the classic path from scikit-learn to deep learning.
Which should you choose?
Choose LLMs from Scratch for genuinely understanding how an LLM works. Choose Hands-On Machine Learning for the classic path from scikit-learn to deep learning.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is LLMs from Scratch or Hands-On Machine Learning easier to use?
Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.
Are LLMs from Scratch and Hands-On Machine Learning free?
LLMs from Scratch is free and open source (Apache-2.0), and Hands-On Machine Learning is free and open source (Apache-2.0). Neither charges for the core software.
Can I run LLMs from Scratch and Hands-On Machine Learning locally?
LLMs from Scratch: yes · Hands-On Machine Learning: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
LLMs from Scratch vs Hands-On Machine Learning — which should I pick in 2026?
Choose LLMs from Scratch for genuinely understanding how an LLM works. Choose Hands-On Machine Learning for the classic path from scikit-learn to deep learning.
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