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followers: 3.8K following: 0.0 repos: 15.0 gists: 0.0

Name: Goku Mohandas

Type: User

Company: @madewithml

Bio: ML @anyscale. Founder @madewithml (acq). AI Research @apple. ML Lead @Ciitizen (acq). Alum @hopkinsmedicine and @gatech

Twitter: GokuMohandas

Location: Cupertino, CA

Blog: https://madewithml.com

Hi, I'm Goku Mohandas

I create platforms that enable people to solve problems.

🔥 We're among the top MLOps repositories on GitHub

GokuMohandas/Made-With-ML: lesson content for Made With ML.
GokuMohandas/mlops-course: repository for the MLOps course.
GokuMohandas/testing-ml: repository for the testing lesson.
GokuMohandas/monitoring-ml: repository for the monitoring lesson.
GokuMohandas/feature-store: repository for the feature store lesson.

Connect with me via Twitter or LinkedIn
to Made With ML for monthly updates on new content!

💻 ML @Anyscale
🌏 Founder @MadeWithML (acq.)
🏥 ML Lead @Ciitizen (acq.)
🔬 AI Research @Apple
🎓 CS/ML @GeorgiaTech
🎓 Biomed @JohnsHopkins

Goku Mohandas's Projects

attentional-interfaces

🔍 Attentional interfaces in TensorFlow.

casual-digressions

💤 Old repository of notes on machine learning papers.

data-engineering

Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.

fast-weights

🏃 Implementation of Using Fast Weights to Attend to the Recent Past.

feature-store

Using a feature store to connect the DataOps and MLOps workflows to enable collaborative teams to develop efficiently.

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gokumohandas

jupyter-config

🌍 Configuration files for Jupyter features.

made-with-ml

Learn how to design, develop, deploy and iterate on production-grade ML applications.

mlops-course

Learn how to design, develop, deploy and iterate on production-grade ML applications.

monitoring-ml

Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.

oreilly-pytorch

🔥 Introductory PyTorch tutorials with OReilly Media.

selu

🤖 Implementation of Self Normalizing Networks (SNN) in PyTorch.

testing-ml

Learn how to create reliable ML systems by testing code, data and models.

the-neural-perspective

📓 Notes from The Neural Perspective (discontinued) blog.

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