Dive into Deep Learning vs 
Made With ML
Dive into Deep Learning vs Made With ML compared for 2026 — features, license, ease of use, performance and which one to choose. The textbook where every equation is runnable vs From notebook to production system.
Updated regularly · curated by OpenSourceAI.tech
Dive into Deep Learning vs Made With ML at a glance
| Spec | Dive into Deep Learning | Made With ML |
|---|---|---|
| Category | Learn AI & machine learning | Learn AI & machine learning |
| Type | Interactive book | Course (MLOps) |
| License | CC-BY-SA-4.0 | MIT |
| Runs locally | Yes | Yes |
| Primary language | Jupyter | Python |
| Ease of use | Intermediate | Intermediate |
| Best for | a rigorous foundation you can actually execute | the gap between a notebook and production |
| GitHub stars | 29.2k | 48.7k |
How Dive into Deep Learning and Made With ML score
| Criterion | Dive into Deep Learning | Made With ML |
|---|---|---|
| Popularity | 3.5 | 4.0 |
| Maintenance | 2.0 | 4.0 |
| Ease of use | 3.5 | 3.5 |
| Privacy | 5.0 | 5.0 |
| License freedom | 3.5 | 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
Dive into Deep Learning
An open textbook used in 500+ universities: every concept comes with maths, runnable code and exercises, available for PyTorch, TensorFlow, JAX and MXNet.
- Adopted by 500+ universities worldwide
- Every equation has runnable code beside it
- Works with PyTorch, TensorFlow and JAX
Made With ML
Goku Mohandas' course on taking ML from a notebook to a reliable production system: testing, CI/CD, monitoring, and the engineering most courses ignore.
- Covers the engineering that courses skip
- Testing, CI/CD and monitoring for ML
- Written by a practitioner, not an academic
Key differences
Dive into Deep Learning is interactive book, while Made With ML is course (MLOps). Their licenses differ (CC-BY-SA-4.0 vs MIT), which matters if you ship a commercial product. In short, Dive into Deep Learning fits a rigorous foundation you can actually execute, and Made With ML fits the gap between a notebook and production.
Which should you choose?
Choose Dive into Deep Learning for a rigorous foundation you can actually execute. Choose Made With ML for the gap between a notebook and production.
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 Dive into Deep Learning or Made With ML easier to use?
Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.
Are Dive into Deep Learning and Made With ML free?
Dive into Deep Learning is free and open source (CC-BY-SA-4.0), and Made With ML is free and open source (MIT). Neither charges for the core software.
Can I run Dive into Deep Learning and Made With ML locally?
Dive into Deep Learning: yes · Made With ML: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
Dive into Deep Learning vs Made With ML — which should I pick in 2026?
Choose Dive into Deep Learning for a rigorous foundation you can actually execute. Choose Made With ML for the gap between a notebook and production.
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