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…
  ☆1,369Updated 9 months ago
• the-full-stack / course-gitbook
  Full Stack Deep Learning Online Course
  ☆906Updated 4 years ago
• Renumics / awesome-open-data-centric-ai
  Curated list of open source tooling for data-centric AI on unstructured data.
  ☆729Updated last year
• 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…
  ☆1,594Updated last week
• xLaszlo / datascience-fails
  Collection of articles listing reasons why data science projects fail.
  ☆465Updated 4 years ago
• eugeneyan / ml-design-docs
  📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)
  ☆621Updated 2 years ago
• chiphuyen / just-pandas-things
  An ongoing list of pandas quirks
  ☆981Updated 2 years ago
• kelvins / awesome-mlops
  A curated list of awesome MLOps tools
  ☆4,780Updated 3 months ago
• davified / clean-code-ml
  Clean Code concepts adapted for machine learning and data science. Now a free video series 😎 https://bit.ly/2yGDyqT
  ☆731Updated 3 years ago
• msaroufim / ml-design-patterns
  Software Architecture for ML engineers
  ☆413Updated 3 years ago
• fuzzylabs / awesome-open-mlops
  The Fuzzy Labs guide to the universe of open source MLOps
  ☆471Updated 5 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.
  ☆340Updated last year
• eugeneyan / ml-surveys
  📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
  ☆2,869Updated 2 years ago
• cdfoundation / sig-mlops
  CDF SIG MLOps
  ☆628Updated 10 months ago
• jphall663 / awesome-machine-learning-interpretability
  A curated list of awesome responsible machine learning resources.
  ☆3,881Updated last month
• firmai / data-science-career
  Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository
  ☆987Updated last year
• ckaestne / seai
  CMU Lecture: Machine Learning In Production / AI Engineering / Software Engineering for AI-Enabled Systems (SE4AI)
  ☆434Updated 2 years ago
• tunguz / ML_Resources
  GitHub Repo with various ML/AI/DS resources that I find useful
  ☆465Updated last year
• Machine-Learning-Tokyo / papers-with-annotations
  Research papers with annotations, illustrations and explanations
  ☆831Updated 4 years ago
• kennethleungty / Failed-ML
  Compilation of high-profile real-world examples of failed machine learning projects
  ☆740Updated last year
• the-full-stack / fsdl-text-recognizer-project
  Lab materials for the Full Stack Deep Learning Course
  ☆1,216Updated 3 years ago
• GokuMohandas / mlops-course
  Learn how to design, develop, deploy and iterate on production-grade ML applications.
  ☆3,208Updated last year
• leehanchung / awesome-full-stack-machine-learning-courses
  Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.
  ☆486Updated 5 months ago
• wandb / awesome-dl-projects
  This is a collection of the code that accompanies the reports in The Gallery by Weights & Biases.
  ☆342Updated 3 years ago
• jacopotagliabue / you-dont-need-a-bigger-boat
  An end-to-end implementation of intent prediction with Metaflow and other cool tools
  ☆871Updated 2 years ago
• mrdbourke / cs329s-ml-deployment-tutorial
  Code and files to go along with CS329s machine learning model deployment tutorial.
  ☆611Updated 2 years ago
• 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.
  ☆1,186Updated 2 years ago
• dair-ai / nlp_paper_summaries
  ✍️ A carefully curated list of NLP paper summaries
  ☆1,480Updated 3 years ago
• explainX / explainx
  Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are look…
  ☆439Updated last year
• jrieke / awesome-machine-learning-startups-berlin
  🤖 A curated list of machine learning & artificial intelligence startups in Berlin (Germany)
  ☆295Updated 2 years ago