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Made-With-ML
GokuMohandas/Made-With-ML
Learn how to develop, deploy and iterate on production-grade ML applications.
★49.0kstars
Jupyter Notebook
MIT
Updated: Today
📋 Project at a Glance
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What's this?A , built with Jupyter Notebook open-source project in the Learning & Resources category, core strengths: data-engineering/data-quality
Who made it?Maintained by GokuMohandas team, 49K⭐ on GitHub, #43 out of 3640 in Learning & Resources
Why does it exist?In the Learning & Resources space, data-engineering workflows faced efficiency bottlenecks. Made-With-ML was built by GokuMohandas to address these data-quality challenges.
What can it do?Key use cases: data-science, deep-learning, distributed-ml
How to install with AI?Use an AI coding assistant to follow the README and automatically handle the install and environment setup.
🔗 github.com/GokuMohandas/Made-With-ML | 官网 https://madewithml.com
🔗 github.com/GokuMohandas/Made-With-ML | 官网 https://madewithml.com
Topics
data-engineeringdata-qualitydata-sciencedeep-learningdistributed-mldistributed-trainingllmsmachine-learningmlopsnatural-language-processingpythonpytorchray