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Flow vs Made With ML

Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.

Flow

Open source · MIT

A static type checker that finds type errors in JavaScript code before it runs.

Full review Website
Made With ML

Open source · MIT

A free course teaching how to build, deploy and maintain machine learning systems with code.

Full review Website

The short answer

Choose Flow if you need…

  • JavaScript developers who want type checking without rewriting their code in another language
  • Teams maintaining large JavaScript codebases that benefit from typed interfaces
  • Developers on macOS, Linux, or Windows who want a prebuilt binary
  • Developers who want to check code in an editor or in CI, as the README describes running the flow binary

Choose Made With ML if you need…

  • Software engineers who want to learn how ML models get deployed and maintained
  • Data scientists who build models but have not shipped them to production
  • College graduates preparing for industry ML roles
  • Product or leadership staff who want a technical foundation for ML projects

Side-by-side

FlowMade With ML
TypeDev toolLearning resource
PriceFree and open sourceFree and open source
LicenceMITMIT
GitHub stars22.3k49.9k
Setup difficultyIntermediateIntermediate
How you get itInstall with a package managerClone and build from source
Main languageRustJupyter Notebook
Last code update4 days ago8 months ago

What each one is

Flow

Flow is a static typechecker for JavaScript, developed by Meta. It reads JavaScript code that has type annotations and reports mismatches, such as passing the wrong kind of value to a function, without running the code. Developers use it to catch bugs earlier and to make large JavaScript codebases easier to understand and change.

Made With ML

Made With ML is a hands-on course, delivered as a GitHub repository of notebooks and Python scripts, that walks through taking a machine learning model from experiment to production. It covers design, development, deployment and iteration, with an emphasis on software engineering practices like testing, logging and serving. The README says the code is meant to run on a personal laptop or on Anyscale clusters.

Best for

Flow

  • JavaScript developers who want type checking without rewriting their code in another language
  • Teams maintaining large JavaScript codebases that benefit from typed interfaces
  • Developers on macOS, Linux, or Windows who want a prebuilt binary
  • Developers who want to check code in an editor or in CI, as the README describes running the flow binary

Made With ML

  • Software engineers who want to learn how ML models get deployed and maintained
  • Data scientists who build models but have not shipped them to production
  • College graduates preparing for industry ML roles
  • Product or leadership staff who want a technical foundation for ML projects

Strengths

Flow

  • Developed and maintained by Meta with a large community and about 22,000 GitHub stars
  • Prebuilt binaries are provided for major platforms, so installation does not require building from source
  • Released under the permissive MIT license

Made With ML

  • Free and open source under the MIT license, with a large community of learners (the README cites 40K+ subscribers)
  • Covers the full lifecycle from experimentation to deployment and iteration in one project
  • Code is organized into clear modules, making it easy to see how the pieces connect

Not ideal for

Flow

  • Projects that already standardized on TypeScript and its tooling, since switching costs time and Flow has a different ecosystem (reason: the README does not compare the two)
  • Beginners with no JavaScript experience, since the tool assumes familiarity with type annotations (reason: the README gives little introductory material and links to external docs)
  • People who want to build Flow themselves on an unsupported platform, since the README lists only macOS arm64, Linux x86_64 and arm64, and Windows x86_64 (reason: limited platform list)

Made With ML

  • People looking only for theory or math, since the README emphasizes practical building over derivations
  • Anyone wanting a ready-made production app to use directly, since this is a teaching project
  • Beginners with no Python experience, because the course assumes working knowledge of Python and ML concepts

Trade-offs

Flow

  • The README is truncated and gives few concrete usage examples; detailed setup is delegated to flow.org
  • Building from source requires a nightly Rust toolchain and, for the JavaScript build, Emscripten, Node, and Yarn
  • The README mentions a Rust port in progress, so parts of the build process may change

Made With ML

  • Setup is more involved than a typical notebook; the README gives separate local and Anyscale instructions and cloud compute is suggested for speed
  • Much of the detailed walkthrough lives on the external course site, so the repository alone may not explain everything
  • The README is truncated and does not show every step, so some setup details are unclear from the text provided

Getting started

Flow

Install nightly Rust toolchain (build from source)

rustup toolchain install nightly

Build the Rust workspace

cd rust_port && cargo +nightly build
Step-by-step guide: how to use Flow

Made With ML

Clone the repository

git clone https://github.com/GokuMohandas/Made-With-ML.git .

Create and activate a virtual environment (local)

python3 -m venv venv # recommend using Python 3.10
Step-by-step guide: how to use Made With ML

Frequently asked questions

What is the difference between Flow and Made With ML?

Flow: A static type checker that finds type errors in JavaScript code before it runs. Made With ML: A free course teaching how to build, deploy and maintain machine learning systems with code. Flow suits javascript developers who want type checking without rewriting their code in another language, while Made With ML suits software engineers who want to learn how ml models get deployed and maintained.

Are Flow and Made With ML free?

Flow: Free and open source. Made With ML: Free and open source.

Is Flow or Made With ML more popular?

Made With ML has more GitHub stars (49.9k) than Flow (22.3k). Popularity isn't the same as fit — check which one matches your use case above.

Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.