https://github.com/GokuMohandas/Made-With-ML

Learn how to design, develop, deploy and iterate on production-grade ML applications.
https://github.com/GokuMohandas/Made-With-ML

data-engineering data-quality data-science deep-learning distributed-ml distributed-training llms machine-learning mlops natural-language-processing python pytorch ray

Last synced: 9 days ago
JSON representation

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

• Host: GitHub
• URL: https://github.com/GokuMohandas/Made-With-ML
• Owner: GokuMohandas
• License: mit
• Created: 2018-11-05T03:44:27.000Z (almost 6 years ago)
• Default Branch: main
• Last Pushed: 2024-08-18T04:34:15.000Z (3 months ago)
• Last Synced: 2024-08-29T03:01:45.708Z (2 months ago)
• Topics: data-engineering, data-quality, data-science, deep-learning, distributed-ml, distributed-training, llms, machine-learning, mlops, natural-language-processing, python, pytorch, ray
• Language: Jupyter Notebook
• Homepage: https://madewithml.com
• Size: 3.82 MB
• Stars: 36,993
• Watchers: 1,224
• Forks: 5,870
• Open Issues: 19
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-list - Made With ML - Learn how to responsibly develop, deploy and maintain production machine learning applications. (Machine Learning Tutorials / Data Management)
• my-awesome - GokuMohandas/Made-With-ML - engineering,data-quality,data-science,deep-learning,distributed-ml,distributed-training,llms,machine-learning,mlops,natural-language-processing,python,pytorch,ray pushed_at:2024-08 star:37.3k fork:5.9k Learn how to design, develop, deploy and iterate on production-grade ML applications. (Jupyter Notebook)