eugeneyan / applyingml
π Papers, guides, and mentor interviews on applying machine learning for ApplyingML.comβthe ghost knowledge of machine learning.
β198Updated 9 months ago
Alternatives and similar repositories for applyingml:
Users that are interested in applyingml are comparing it to the libraries listed below
- π Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.β145Updated 11 months ago
- Toy example of an applied ML pipeline for me to experiment with MLOps tools.β207Updated 3 years ago
- π Minimal examples of machine learning tests for implementation, behaviour, and performance.β261Updated 2 years ago
- Interview Questions and Answers for Machine Learning Engineer roleβ118Updated 2 years ago
- Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).β96Updated 2 years ago
- Blogs on Machine Learning and Deep learningβ110Updated 3 years ago
- β38Updated 3 years ago
- π§ͺ Simple data science experimentation & tracking with jupyter, papermill, and mlflow.β179Updated 8 months ago
- π Curated list of machine learning engineering blogs.β39Updated 4 months ago
- Machine Learning begins with Human Learningβ108Updated 3 years ago
- Kaggle Pipeline for tabular data competitionsβ204Updated 8 months ago
- Software Architecture for ML engineersβ398Updated 2 years ago
- π Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)β583Updated 2 years ago
- An assignment for CMU CS11-711 Advanced NLP, building NLP systems from scratchβ171Updated 2 years ago
- ML Research paper summaries, annotated papers and implementation walkthroughsβ114Updated 3 years ago
- A curated list of awesome fastai projects/blog posts/tutorials/etc.β167Updated 3 years ago
- 100 exercises to learn Python Datatableβ268Updated 3 years ago
- Curriculum and roadmap from 0 to Mastery for MLOps. Adding value to your machine learning model by deploying it for people to use it to sβ¦β182Updated 3 years ago
- Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflowβ237Updated last year
- Source of the FSDL 2022 labs, which are at https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022-labsβ81Updated last year
- Learn how to create reliable ML systems by testing code, data and models.β86Updated 2 years ago
- Practical Deep Learning at Scale with MLFlow, published by Packtβ159Updated last year
- Machine Learning / Deep Learning Environment. Everywhere. Anywhere.β50Updated 4 years ago
- β144Updated 3 years ago
- Real data science interview assignmentsβ94Updated 4 years ago
- Code and files to go along with CS329s machine learning model deployment tutorial.β605Updated 2 years ago
- π¬ Sharing your data science notebooks with the community has never been this easy.β38Updated 2 years ago
- GitHub Repo with various ML/AI/DS resources that I find usefulβ461Updated 8 months ago
- Metaflow tutorials for ODSC West 2021β64Updated 3 years ago
- Code samples for the Effective Data Science Infrastructure bookβ115Updated last year