Made With ML

Applied ML · MLOps · Production

Join 40K+ developers in learning how to responsibly develop, deploy & maintain ML.

🏆 Among the top ML repositories on GitHub.

🛠️ Highly recommended industry resource.

Foundations

Learn the foundations of machine learning through intuitive explanations, clean code and visualizations. → GokuMohandas/Made-With-ML

1. 🛠 Toolkit

2. 🔥 Machine Learning

3. 🤖 Deep Learning

MLOps course

Learn how to combine machine learning with software engineering to develop, deploy & maintain production ML applications. → GokuMohandas/mlops-course

1. 🎨 Design

2. 🔢 Data

3. 📈 Modeling

4. 💻 Developing

5. 📦 Serving

6. ✅ Testing

7. ♻️ Reproducibility

8. 🚀 Production

9. ⎈ Data engineering

Principles

Every lesson is written with the following principles:

Intuition-first

We never jump straight to code, instead we develop an intuition for the concepts first.

Hands-on

Instead of just discussing MLOps concepts, we code everything (project-based).

Engineering

It's not just about ML, it's also about software engineering best practices.

Comprehensive

Lessons easily extend across different algorithms, data modalities, tech stacks, etc.

Meet your instructor

Hi, I'm Goku Mohandas

Over the past 7 years, I've worked on ML at a large company (NLP & ML platform @Apple), a startup in the oncology space (led the ML team @Ciitizen [acquired]) and ran my own startup in the rideshare space (HotSpot). Throughout my journey, I've worked with brilliant engineering and product teams and learned how to responsibly develop, deploy and iterate on ML systems across various industries, stacks and scale.

I currently work closely with teams from early-stage/F500 companies in helping them develop, deploy and maintain production ML applications while diving into the best and bespoke practices of this rapidly evolving space. I also collaborate with the best tooling/platform companies who share our mission of making responsible ML easier and faster. I want to share this knowledge with the rest of the world so we can accelerate progress in this space.

ML is not a separate industry, instead, it's a powerful way of thinking about data, so let's make sure we have a solid foundation before we start changing the world with it. Made With ML is our medium to catalyze this goal and though we're off to great start, we still have a long way to go.

❤️ Wall of Love

See what the community has to say about Made With ML.

Sherry Wang

Senior ML Engineer - Cars.com

"Made with ML is one of the best courses I’ve ever taken. The material covered is very practical; I get to apply some of them to my job right away."

Deepak Jayakumaran

Lead Data Scientist - Grab

"This course has given me the know-how to make optimal choices around design & implementation of ML engineering for a variety of real-world use-cases."

Jeremy Jordan

Senior ML Engineer - Duo Security

"This will be a great journey for those interested in deploying machine learning models which lead to a positive impact on the product."

Clara Matos

Lead AI Engineer - Sword Health

"This course really mimics the production ML thought process by providing alternative options with different levels of complexity & weighing on the pros/cons."

Ritchie Ng

PyTorch Keynote Speaker

"For production ML, I cannot possibly think of a better resource out there ... this resource is the gold standard."

Daniel Bourke

Founder - Mrdbourke

"Built some machine learning models? Want to take them to the next level? I do. And I’m using @madewithml to learn how. Outstanding MLOps lessons!"

Kavin Veerapandian

Senior Analyst - Citi

"Coming from academia with purely model-specific knowledge, Made With ML set the expectations right when it comes to how ML is being applied in the industry."

Karthik Bhaskar

Senior Data Scientist - CIBC

"Best available practical course on MLOps. Thanks @GokuMohandas for creating such awesome content and sharing it!"

Dmitry Petrov

Co-Founder, CEO - DVC

"This is not a usual ML class, it covers productionalization part of ML projects - the most important part from a business point of view."

Lawrence Okegbemi

ML Engineer - Enterscale

"Following all through, it's really amazing to see how you demonstrated best practices in building an ML driven application."

Laxman Tomar

ML Engineer - Robofied

"The best MLOps resource that I've come across on the web. Goes over whys, hows, tradeoffs, tools & their alternatives via high-quality explanations and code."

Satyabrata Pal

Julia Community

"Completely sold out on the clean code and detailed writeup. This is one of the few ML courses which doesn't stop on just training a model but goes beyond."

Peter Ku

Senior ML Engineering - Amazon

"Covers the broad MLOps landscape in great detail, extremely high quality tested code and not just talking about concepts on a high level, open-sourced."

Abinaya Mahendiran

Data Science Manager - Mphasis

"For anyone interested in seeing MLOps in action, this is the best practical resource out there! Thank you for this wonderful course. Highly recommended!"

Ash Katnoria

Software Eng - Bank of Scotland

"Easily one of the most comprehensive series. I am amazed by how much ground it covers starting with data collection, all the way up to k8s + model monitoring."

Arghyadeep Das

Software Engineer - Barclays

"Ideal place for grad students and software engineers to learn about practical ML. Couldn't have a better resource collection than this!"

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To cite this content, please use:

@article{madewithml,
    author       = {Goku Mohandas},
    title        = { Home - Made With ML },
    howpublished = {\url{https://madewithml.com/}},
    year         = {2022}
}