Alternatives and similar repositories for awesome-seml

Users that are interested in awesome-seml are comparing it to the libraries listed below

• EthicalML / awesome-artificial-intelligence-regulation
  This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and b…
  ☆1,347Updated 6 months ago
• the-full-stack / course-gitbook
  Full Stack Deep Learning Online Course
  ☆901Updated 3 years ago
• superlinear-ai / awesome-machine-learning-engineer
  🤓 A curated awesome list of Machine Learning Engineering resources. Feel free to contribute!
  ☆290Updated 9 months ago
• neomatrix369 / awesome-ai-ml-dl
  Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources o…
  ☆1,564Updated 3 weeks ago
• davified / clean-code-ml
  Clean Code concepts adapted for machine learning and data science. Now a free video series 😎 https://bit.ly/2yGDyqT
  ☆727Updated 3 years ago
• wandb / awesome-dl-projects
  This is a collection of the code that accompanies the reports in The Gallery by Weights & Biases.
  ☆341Updated 3 years ago
• xLaszlo / datascience-fails
  Collection of articles listing reasons why data science projects fail.
  ☆465Updated 4 years ago
• Renumics / awesome-open-data-centric-ai
  Curated list of open source tooling for data-centric AI on unstructured data.
  ☆721Updated last year
• msaroufim / ml-design-patterns
  Software Architecture for ML engineers
  ☆411Updated 3 years ago
• chiphuyen / just-pandas-things
  An ongoing list of pandas quirks
  ☆974Updated 2 years ago
• mrdbourke / cs329s-ml-deployment-tutorial
  Code and files to go along with CS329s machine learning model deployment tutorial.
  ☆607Updated 2 years ago
• eugeneyan / ml-design-docs
  📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)
  ☆615Updated 2 years ago
• fuzzylabs / awesome-open-mlops
  The Fuzzy Labs guide to the universe of open source MLOps
  ☆470Updated 2 months ago
• ckaestne / seai
  CMU Lecture: Machine Learning In Production / AI Engineering / Software Engineering for AI-Enabled Systems (SE4AI)
  ☆430Updated 2 years ago
• Machine-Learning-Tokyo / papers-with-annotations
  Research papers with annotations, illustrations and explanations
  ☆829Updated 4 years ago
• zszazi / Deep-learning-in-cloud
  List of Deep Learning Cloud Providers
  ☆789Updated 3 months ago
• kelvins / awesome-mlops
  A curated list of awesome MLOps tools
  ☆4,644Updated 3 weeks ago
• leehanchung / awesome-full-stack-machine-learning-courses
  Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.
  ☆474Updated 2 months ago
• Nachimak28 / awesome-list-of-awesomes
  A curated list of all the Awesome --Topic Name-- lists I've found till date relevant to Data lifecycle, ML and DL.
  ☆339Updated last year
• The-AI-Summer / Deep-Learning-In-Production
  Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
  ☆1,171Updated 2 years ago
• cdfoundation / sig-mlops
  CDF SIG MLOps
  ☆625Updated 8 months ago
• the-full-stack / fsdl-text-recognizer-project
  Lab materials for the Full Stack Deep Learning Course
  ☆1,212Updated 3 years ago
• Machine-Learning-Tokyo / Math_resources
  ☆345Updated 4 years ago
• jacopotagliabue / you-dont-need-a-bigger-boat
  An end-to-end implementation of intent prediction with Metaflow and other cool tools
  ☆868Updated 2 years ago
• 1duo / awesome-ai-infrastructures
  Infrastructures™ for Machine Learning Training/Inference in Production.
  ☆420Updated 6 years ago
• jrieke / awesome-machine-learning-startups-berlin
  🤖 A curated list of machine learning & artificial intelligence startups in Berlin (Germany)
  ☆293Updated 2 years ago
• dair-ai / d2l-study-group
  🧠 Material for the Deep Learning Study Group
  ☆394Updated 3 years ago
• eugeneyan / ml-surveys
  📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
  ☆2,862Updated 2 years ago
• kabartay / OpenUnivCourses
  FREE ML Courses from Top Universities in CS
  ☆249Updated last year
• GokuMohandas / mlops-course
  Learn how to design, develop, deploy and iterate on production-grade ML applications.
  ☆3,167Updated 11 months ago