Who Am I

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💁🏻‍♀️ Sr ML Ops Engineer 💌 Developer Advocate & Content Creator 🏂 Building full-stack ML apps + platforms

I'm a practicing Sr MLOps Engineer that advocates & creates educational content for practitioners & entrepreneurs looking to build full-stack ML applications.

My goal is to demystify MLOps & show how to develop high-quality ML products from scratch from a vendor & architecture agnostic perspective.

This means:

✅ Developing scalable, resilient, & reliable production ML systems for companies like Mailchimp;

✅ Creating books, videos, courses, & workshops to teach MLOps best practices & architectures;

✅ Contributing thought leadership around applied ML through organizations like Nvidia;

✅ Hacking projects (both open-source & personal) using best-of-breed tools & practices from software engineering, DevOps, data engineering, & machine learning using Python, SQL, Solidity, GCP, Docker, Kubernetes, etc.

Prior to Mailchimp's ML Ops team I was with Sidewalk.ai 🏘 (leveraging MLE+Ops to build enablement tools for residential real estate agents), @Teladoc , @WalkMe , @Autodesk, and @Sunrun. 🌻


Stuff I've Written

Break into {X}

Data Science:

➡️ ✂️Breaking into Data Science- From Hair Salon to Data Scientist (Ch.1)🔍

➡️ 💈 Breaking into Data Science — Upskilling & Bootcamps (Ch.2)- 📊

➡️ ✂️ Breaking into Data Science — Applying & Interviewing (Ch.3)- 🔍

➡️ ✂️Breaking into Data Science — Getting the DS Offer & Next Steps (Ch.4)🔍

ML Engineering:

➡️ 👩🏻‍💻 Miki’s 🔥Hot-Takes🔥 on MLE Interviews: Types of Roles & Interview Prep (Part 1/2)

➡️ 👩🏻‍💻 Miki’s 🔥Hot-Takes🔥 on MLE Interviews: Top Advice & Resources (Part 2/2)

Effective Software Engineering for Data Science

➡️ Understanding the “Why” of VM’s, Containers, & Virtual Environments

Deep Dives

➡️ An Easy Introduction to Speech AI w/ @nvidia


Other Places to Find Me

👩🏻‍🏫 LinkedIn: https://www.linkedin.com/in/mikikobazeley

📹 Youtube: https://bit.ly/3MBR8N3

🐥 Twitter: https://twitter.com/BazeleyMikiko

🐙🐈 Github: https://github.com/MMBazel

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I show you how to build ML systems, applications, and MLOps platforms.

People

👩🏻‍💻 {Helping MLOps teams build platforms} + {Data Scientists get models into production} 🤖