Alternatives and similar repositories for datascience-fails:

Users that are interested in datascience-fails are comparing it to the libraries listed below

• dynamicwebpaige / kaggle-survey-spelunking
  ☆145Updated 3 years ago
• shreyashankar / toy-ml-pipeline
  Toy example of an applied ML pipeline for me to experiment with MLOps tools.
  ☆208Updated 3 years ago
• koaning / doubtlab
  Doubt your data, find bad labels.
  ☆511Updated 9 months ago
• ttzt / catalog_of_requirements_for_ai_products
  The purpose of the catalog is to help data science teams to collect all the requirements to consider while building a ML model and produc…
  ☆129Updated 4 years ago
• eugeneyan / papermill-mlflow
  🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.
  ☆182Updated 9 months ago
• vopani / datatableton
  100 exercises to learn Python Datatable
  ☆268Updated 3 years ago
• koaning / human-learn
  Natural Intelligence is still a pretty good idea.
  ☆808Updated 9 months ago
• chiphuyen / just-pandas-things
  An ongoing list of pandas quirks
  ☆959Updated last year
• eugeneyan / ml-design-docs
  📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)
  ☆590Updated 2 years ago
• dabl / dabl
  Data Analysis Baseline Library
  ☆727Updated 4 months ago
• dslp / dslp
  The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process …
  ☆507Updated 4 years ago
• data-describe / data-describe
  data⎰describe: Pythonic EDA Accelerator for Data Science
  ☆300Updated 2 years ago
• eugeneyan / testing-ml
  🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.
  ☆263Updated 2 years ago
• loglabs / mltrace
  Coarse-grained lineage and tracing for machine learning pipelines.
  ☆469Updated 2 years ago
• MBrouns / timeseers
  Time should be taken seer-iously
  ☆315Updated 2 years ago
• ericmjl / essays-on-data-science
  In which I put together my thoughts on the practice of data science.
  ☆296Updated last year
• eugeneyan / python-collab-template
  🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.
  ☆146Updated last year
• bgweber / DS_Production
  ☆154Updated 4 years ago
• davified / clean-code-ml
  Clean Code concepts adapted for machine learning and data science. Now a free video series 😎 https://bit.ly/2yGDyqT
  ☆724Updated 3 years ago
• alegonz / baikal
  A graph-based functional API for building complex scikit-learn pipelines.
  ☆590Updated 2 years ago
• jessicayung / machine-learning-flashcards
  Machine learning flashcards
  ☆221Updated 3 years ago
• drivendataorg / deon
  A command line tool to easily add an ethics checklist to your data science projects.
  ☆295Updated 9 months ago
• ericmjl / bayesian-analysis-recipes
  A collection of Bayesian data analysis recipes using PyMC3
  ☆557Updated last year
• FilippoBovo / production-data-science
  Production Data Science: a workflow for collaborative data science aimed at production
  ☆453Updated 4 years ago
• jmugan / modern_practical_nlp
  This course covers how you can use NLP to do stuff.
  ☆267Updated 4 years ago
• amueller / COMS4995-s20
  COMS W4995 Applied Machine Learning - Spring 20
  ☆245Updated 3 years ago
• msaroufim / ml-design-patterns
  Software Architecture for ML engineers
  ☆403Updated 2 years ago
• ing-bank / popmon
  Monitor the stability of a Pandas or Spark dataframe ⚙︎
  ☆500Updated 3 months ago
• bodywork-ml / bodywork-core
  ML pipeline orchestration and model deployments on Kubernetes.
  ☆435Updated last year
• eugeneyan / applyingml
  📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.
  ☆199Updated 11 months ago