End-to-End MLOps Projects and Learning Materials for Your Portfolios
Exploring the projects that could take your data science skill to the next level
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🔥Benefit Time: A lot of Time🔥
Recently, companies and businesses have realized how important data is and their derivate application to their business. The realization comes from how data science and machine learning have created more value compared to the past, especially with how easily we process data in modern times.
However, if we know the data, they would constantly change. This means that the data project cannot be a one-time activity, and we hope the model brings value forever.
That’s where MLOps comes in. By managing and automating the model, businesses can achieve constant values without sacrificing too much time.
Given how important MLOps is to business, the skills have become sought after, and businesses are willing to pay a lot for talented data scientists with MLOps skills. The salary range for an MLOps engineer can cross $100K annually, which is a lot.
So, let’s prepare ourselves with a collection of MLOps project portfolios and learning materials.
If you are interested, I have previously written about MLOps Basic Open-Source Tool, which you might want to check out. I will try to continue writing about it at some point.
MLOps Basic Open-Source Tool Series #1: MLflow for Experiment Tracking and Model Management
This newsletter is part of a series introducing open-source tools used in Machine Learning Operations (MLOps). Each series will introduce new tools for different parts of the process. We would combine everything at the end of the series to make a cohesive MLOps project.
With that in mind, let’s get into it!
MLOps Projects to Learn from
Let’s start with the project portfolios I deem beneficial. Most of them are simple and easy to follow, yet they would improve your MLOps skills.
Although, I would start with the MLOps template rather than the project itself.
👉The MLOps Cookiecutter by Chayma Zatout
So, it’s a template of the MLOps project based on Chayma's article about MLOps for beginners. Cookiecutter is an open-source package to standardize project templates. Chayma created a nice template for us to develop the MLOps structure; we only need to fill it out with all the details.
Next, I would shamelessly plug in my articles to help you learn about MLOps.
👉Simple Model Retraining Automation via GitHub Actions by Cornellius Yudha Wijaya
👉End-to-End Spam Classifier by Cornellius Yudha Wijaya
These projects would teach you hands-on how to develop data science projects with MLOps in mind. I am using open-source data that you change to your own dataset.
Also, you guys should not miss my favourite end-to-end MLOps project.
👉Build E2E CICD Pipeline with GitHub Actions, Docker, and Cloud by Ronil Patil
👉End to end machine learning: MLOps Recommendation system by Minh-Hai Tran
👉Capital Bike Share MLOps Project by Walukagga Patrick
👉Reservation Cancellation Forecasting by Jeremy Arancio
👉MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK
Those are some awesome MLOps End-to-End projects you should see and learn from.
However, some of you might want to learn the basics before creating that MLOps project.
So, here are some learning materials you should check out!
FREE MLOps Learning Material
Here are some of the best MLOps materials I know would help you upskill yourself.
It’s a 9-week MLOps study plan for you to follow. You would learn much about MLOps from Model Monitoring, Data Versioning, Model Packaging, Docker, and many more.
🚀Made with ML by Goku Mohandas
This is one of the best FREE MLOps out there. The learning material comprises various concepts and hands-on approaches to operationalizing ML workflows and integrating them with many MLOps tools.
Collection of FREE MLOps online resources. It includes YouTube, blogs, books, courses, projects, etc.
Let’s return to the basics of MLOps. The guide website will take you to explore the principles and implementation of MLOps in the industry.
🚀MLOps Zoomcamp by DataTalks.Club
FREE MLOps courses with Cohort and Self-Paced teaching teach the practical aspects of productionizing ML services—from training and experimenting to model deployment and monitoring. They’re targeted at beginners and professionals who want to upskill themselves.
The Technical University of Denmark, or DTU, offers an amazing course about MLOps, and they share the material for FREE! The course covers all the basics you need for MLOps.
That’s all for the Learning Material. I hope your MLOps journey is going strong🔥!
What do you think? Do you want me to write more about the MLOps content even deeper? Share and discuss it together in the comment below.👇
Articles to Read
Here are some of my latest articles you might miss this week.
🤩Also, here are some of my favorite readings of the week.
My Success Secrets: Turning Small Moves Into Big Outcomes by
Understanding Hugging Face - The AI Community's Open-Source Oasis 🤗🏝️ by
New LLM Pre-training and Post-training Paradigms by
The 10-Minute Habit That Transformed My Tech Leadership by
Cheers!
Personal Notes
If you know me, I am an avid gamer (from console, arcade, to board games, I am into everything). In my spare time, I often spend time finishing my long list of RPG games.
And you know what? I am proud to finish my first Baldur’s Gate 3 Playthrough after 100+ hours spent on the game. I know the game has been released since last year, but what is important is the feeling of concluding the story.
I don’t know how many subscribers here are playing games on the console or PC, but I don’t mind as well if you guys want to discuss the game.
Thanks for including my post.
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