Alternatives and similar repositories for talks

Users that are interested in talks are comparing it to the libraries listed below

• soda-inria / survival-analysis-benchmark
  Exploratory repository to study predictive survival analysis models
  ☆37Updated 2 years ago
• iterative / VSCode-DVC-Workshop
  Workshop about DVC VSCode Extension
  ☆13Updated last year
• NatanMish / data_validation
  Tutorial for implementing data validation in data science pipelines
  ☆33Updated 3 years ago
• unravelin / code-test-data-science
  Data Scientist code test
  ☆19Updated 5 years ago
• jphall663 / hc_ml
  Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
  ☆22Updated 5 years ago
• wimlds / berlin-ds-lab
  WiMLDS Berlin Data Science Lab
  ☆17Updated 7 months ago
• ronikobrosly / scipy_2022_causal_inference_tutorial
  A set of decks and notebooks with exercises for use in a hands-on causal inference tutorial session
  ☆32Updated 3 years ago
• jphall663 / GWU_rml
  ☆39Updated 5 months ago
• edublancas / ml-testing
  🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects
  ☆82Updated 3 years ago
• outerbounds / full-stack-ML-metaflow-tutorial
  It's all in the name
  ☆81Updated 2 years ago
• DataForScience / Graphs4Sci
  ☆48Updated last year
• normconf / awesome-normconf
  List of resources coming out of Normconf Slack
  ☆76Updated 2 years ago
• koaning / icepickle
  It's a cooler way to store simple linear models.
  ☆27Updated last year
• coiled / data-science-at-scale
  A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using th…
  ☆117Updated 2 years ago
• jacopotagliabue / no-ops-machine-learning
  A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.
  ☆37Updated 4 years ago
• summerscope / fair-ml-reading-group
  Reading history for Fair ML Reading Group in Melbourne
  ☆36Updated 4 years ago
• bodywork-ml / ml-pipeline-engineering
  Best practices for engineering ML pipelines.
  ☆36Updated 3 years ago
• nhsx / skunkworks-synthetic-data
  A pipeline for generating and evaluating synthetic data generation models. Currently using SynthVAE to demonstrate functionality. Read mo…
  ☆26Updated 3 years ago
• Isaac-Flath / QuartoTemplates
  ☆20Updated 3 years ago
• tdpetrou / integrating-pandas-with-scikit-learn
  Tutorial covering a new workflow available going from pandas to scikit-learn
  ☆39Updated 2 years ago
• formlio / forml
  ForML - A development framework and MLOps platform for the lifecycle management of data science projects
  ☆106Updated 2 years ago
• FlorianWilhelm / polars_vs_pandas
  Comparing Polars to Pandas and a small introduction
  ☆44Updated 4 years ago
• data-max-hq / ab-testing-in-ml
  Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.
  ☆40Updated 9 months ago
• PAIR-code / datacardsplaybook
  The Data Cards Playbook helps dataset producers and publishers adopt a people-centered approach to transparency in dataset documentation.
  ☆195Updated last year
• ploomber / projects
  Sample projects using Ploomber.
  ☆86Updated last year
• jseabold / pandas-selectable
  A `select` accessor for easier subsetting of pandas DataFrames and Series
  ☆34Updated 2 years ago
• AidanCooper / shap-clustering
  How to use SHAP values for better cluster analysis
  ☆59Updated 3 years ago
• khuyentran1401 / prefect-docker
  Demo on how to use Prefect with Docker
  ☆27Updated 3 years ago
• AllenDowney / SurvivalAnalysisPython
  Explorations of survival analysis in Python
  ☆50Updated 2 years ago
• noahgift / or
  Operations Research Algorithms
  ☆18Updated last year