eugeneyan / applyingml
π Papers, guides, and mentor interviews on applying machine learning for ApplyingML.comβthe ghost knowledge of machine learning.
β197Updated 7 months ago
Alternatives and similar repositories for applyingml:
Users that are interested in applyingml are comparing it to the libraries listed below
- Toy example of an applied ML pipeline for me to experiment with MLOps tools.β207Updated 3 years ago
- Interview Questions and Answers for Machine Learning Engineer roleβ118Updated 2 years ago
- π Minimal examples of machine learning tests for implementation, behaviour, and performance.β258Updated 2 years ago
- Machine Learning begins with Human Learningβ108Updated 3 years ago
- β38Updated 3 years ago
- Blogs on Machine Learning and Deep learningβ109Updated 3 years ago
- Software Architecture for ML engineersβ393Updated 2 years ago
- ML Research paper summaries, annotated papers and implementation walkthroughsβ114Updated 2 years ago
- π Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.β145Updated 9 months ago
- An assignment for CMU CS11-711 Advanced NLP, building NLP systems from scratchβ169Updated 2 years ago
- 100 exercises to learn Python Datatableβ269Updated 3 years ago
- A curated list of awesome fastai projects/blog posts/tutorials/etc.β165Updated 3 years ago
- π Curated list of machine learning engineering blogs.β35Updated 2 months ago
- Kaggle Pipeline for tabular data competitionsβ204Updated 6 months ago
- π Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)β571Updated last year
- 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¦β184Updated 2 years ago
- Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflowβ234Updated last year
- Supplementary Materials for the Deep Learning Book by Ian Goodfellow et alβ53Updated 2 years ago
- Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).β96Updated 2 years ago
- Learn how to create reliable ML systems by testing code, data and models.β85Updated 2 years ago
- π² A curated list of MLOps projects, tools and resourcesβ185Updated 8 months ago
- Practical Deep Learning at Scale with MLFlow, published by Packtβ159Updated last year
- Machine Learning / Deep Learning Environment. Everywhere. Anywhere.β50Updated 4 years ago
- π§ͺ Simple data science experimentation & tracking with jupyter, papermill, and mlflow.β177Updated 6 months ago
- Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.β80Updated 2 years ago
- Real data science interview assignmentsβ94Updated 4 years ago
- Coarse-grained lineage and tracing for machine learning pipelines.β467Updated 2 years ago
- 100 applications built with H2O Waveβ99Updated 2 years ago