Made With ML
Applied ML · MLOps · Production
Join 35K+ developers in learning how to responsibly deliver value with ML.
"For production ML, I cannot possibly think of a better resource out there ... this resource is the gold standard."
"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!"
"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."
"Ideal place for grad students and software engineers to learn about practical ML. Couldn't have a better resource collection than this!"
"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."
"For anyone interested in seeing MLOps in action, this is the best practical resource out there! Thank you for this wonderful course. Highly recommended!"
"This will be a great journey for those interested in deploying machine learning models which lead to a positive impact on the product."
"Best available practical course on MLOps. Thanks @GokuMohandas for creating such awesome content and sharing it!"
"This is not a usual ML class, it covers productionalization part of ML projects - the most important part from a business point of view."
"Following all through, it's really amazing to see how you demonstrated best practices in building an ML driven application."
"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."
"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 that."
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Features
We never jump straight to code, instead we develop an intuition for the concepts first.
Instead of just discussing MLOps concepts, we code everything (project-based).
It's not just about ML, it's also about software engineering best practices.
Easily extends to all algorithms, data (text, image, tabular), tools, cloud providers, etc.
Foundations
Learn the foundations of machine learning through intuitive explanations, clean code and visualizations. → GokuMohandas/Made-With-ML
MLOps course
Learn how to apply ML to build a production grade product and deliver value. → GokuMohandas/mlops-course
📦 Purpose
🔢 Data
📈 Modeling
💻 Developing
📦 Serving
✅ Testing
♻️ Reproducibility
🚀 Production
Who is this content for?
Machine learning is not a separate industry, instead, it's a powerful way of thinking about data that's not reserved for any one type of person.
looking to learn ML and become even better software engineers. ML is integrated into increasingly more products so it's important to know how ML systems operate.
who want to want to go way beyond developing models in a notebook to wrapping them around robust workflows that enable ML systems to improve over time.
looking to learn the practical skills they'll need for the industry and bridge gap between their university curricilum and what industry expects them to know about ML systems.
who want to develop a technical foundation in MLOps so they can effectively communicate with their technical team and help develop and iterate on applications.
Meet your instructor
Hi, I'm Goku Mohandas
Over the past 7 years, I've worked on ML and product at a large company (Apple), a startup in the oncology space (Ciitizen) and ran my own startup in the rideshare space (HotSpot). Throughout my journey, I've worked with brilliant developers and product managers and learned how to responsibly develop, deploy and iterate on ML systems across various industries.
I currently work closely with early-stage and mid-sized companies in helping them deliver value with ML while diving into the best and bespoke practices of this rapidly evolving space. 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. 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.
To cite this content, please use:
| @misc{madewithml,
author = {Goku Mohandas},
title = {Made With ML},
howpublished = {\url{https://madewithml.com/}},
year = {2021}
}
|
