Alternatives and similar repositories for PyTestforDataScience_PyDataLA

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

• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated last year
• amueller / aml
  Applied Machine Learning with Python
  ☆80Updated last year
• ryanmark1867 / deep_learning_for_structured_data
  Production repo to accompany Deep Learning with Structured Data book from Manning: https://www.manning.com/books/deep-learning-with-struc…
  ☆73Updated 4 years ago
• tklouie / PyData_LA_2018
  Added repo for PyData LA 2018 tutorial
  ☆88Updated 7 years ago
• DunderData / Tutorials
  Python data science and machine learning from Ted Petrou with Dunder Data
  ☆55Updated 3 years ago
• Vishwacorp / nyc_uber_forecasting
  Forecasting Uber demand in NYC neighborhoods
  ☆34Updated 7 years ago
• htorrence / pytest_examples
  Reference package for unit tests
  ☆49Updated 7 years ago
• dziganto / Data_Science_Fundamentals
  ☆101Updated 7 years ago
• eugeneyan / papermill-mlflow
  🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.
  ☆184Updated last year
• StevenMMortimer / ge-sklearn-pipeline-example
  Example using Great Expectations to Validate Data in a scikit-learn Pipeline
  ☆21Updated 5 years ago
• jrzaurin / ml-pipeline
  Using Kafka-Python to illustrate a ML production pipeline
  ☆112Updated 3 years ago
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆65Updated 3 years ago
• outerbounds / dsbook
  Code samples for the Effective Data Science Infrastructure book
  ☆116Updated 2 years ago
• MaartenGr / ML-API
  Guide on creating an API for serving your ML model
  ☆65Updated 3 years ago
• amueller / dabl
  Data Analysis Baseline Library
  ☆133Updated last year
• joelcthomas / modeldrift
  Capturing model drift and handling its response - Example webinar
  ☆108Updated 6 years ago
• AlexIoannides / ml-workflow-automation
  Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deploym…
  ☆65Updated 2 years ago
• trainindata / testing-and-monitoring-ml-deployments
  Example project for the course "Testing & Monitoring Machine Learning Model Deployments"
  ☆135Updated last year
• juanitorduz / ml_prod_tutorial
  Explore tips and tricks to deploy machine learning models with Docker.
  ☆13Updated 2 years ago
• dkhundley / ds-quick-tips
  Data Science Quick Tips Repository!
  ☆48Updated last year
• tdpetrou / integrating-pandas-with-scikit-learn
  Tutorial covering a new workflow available going from pandas to scikit-learn
  ☆40Updated 3 years ago
• schmidtbri / simple-ml-model-abc
  Code demonstrating a simple Machine Learning model abstract base class and its uses.
  ☆14Updated 2 years ago
• yoonkanglow / Causal-Impact-Analysis-Demo
  ☆26Updated 8 years ago
• bgweber / DS_Production
  ☆155Updated 5 years ago
• xLaszlo / CQ4DS-notebook-sklearn-refactoring-exercise
  ☆31Updated 2 years ago
• solegalli / Python-Feature-Engineering-Cookbook-First-Edition
  ☆32Updated last year
• klemag / pydata_nyc2018-intro-to-model-interpretability
  Notebook and slides for my talk at Pydata NYC 2018
  ☆88Updated last year
• klemag / pydataLDN_2019-maintainable-code-for-data-science
  ☆47Updated 6 years ago
• AllenDowney / SurvivalAnalysisPython
  Explorations of survival analysis in Python
  ☆50Updated 2 years ago
• docker-for-data-science / docker-for-data-science-tutorial
  Materials for "Docker for Data Science" tutorial presented at PyCon 2018 in Cleveland, OH
  ☆160Updated 5 years ago