jesford / testing-in-data-science
Intro to Testing in Data Science Tutorial
☆35Updated 2 years ago
Alternatives and similar repositories for testing-in-data-science:
Users that are interested in testing-in-data-science are comparing it to the libraries listed below
- Today I Learned Some Computer Stuff☆39Updated 6 years ago
- ☆15Updated 6 years ago
- Tutorial covering a new workflow available going from pandas to scikit-learn☆40Updated 2 years ago
- Workshop on Target Leakage in Machine Learning I taught at ODSC Europe 2018 (London) and ODSC East 2019, 2020 (Boston)☆37Updated 4 years ago
- Comparing Polars to Pandas and a small introduction☆43Updated 3 years ago
- Bayesian statistics seminars☆30Updated 7 years ago
- Know your ML Score based on Sculley's paper☆34Updated 5 years ago
- Crestle version of fast.ai courses☆14Updated 7 years ago
- Code and notebooks for a talk given at PyBay, 2018-08-19☆48Updated 3 years ago
- ☆28Updated 7 years ago
- A bit of extra usability for sqlalchemy v2.☆77Updated 9 months ago
- Mini module with syntax sugar for pandas/sklearn☆107Updated 4 years ago
- A machine learning testing framework for sklearn and pandas. The goal is to help folks assess whether things have changed over time.☆102Updated 3 years ago
- Exploratory code to see if we can learn about feature relationships in a DataFrame using machine learning☆55Updated 5 years ago
- A repository for public storage of slides given at the 17th Python in Science Conferences (2018)☆134Updated 5 years ago
- State management framework for Data Science & Analytics☆19Updated 5 years ago
- Introduction to web scraping and text mining☆48Updated 5 years ago
- Data Scientist code test☆19Updated 4 years ago
- A `select` accessor for easier subsetting of pandas DataFrames and Series☆34Updated last year
- 📈 Interactive comparison of Python plotting libraries for exploratory data analysis. Examples of using Pandas plotting, plotnine, Seabor…☆108Updated 3 years ago
- Data exploration library with a pandas-like API☆74Updated 4 years ago
- JupyterCon 2018 JupyterLab tutorial☆21Updated 6 years ago
- ☆15Updated 2 years ago
- Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference☆25Updated 5 years ago
- Inspired by John Foreman. Created by the crowds.☆54Updated last year
- Automated Exploratory Data Analysis. Simplifying Data Exploration☆34Updated 4 years ago
- Contains benchmarking and interpretability experiments on the Adult dataset using several libraries☆35Updated 5 years ago
- Common post-estimation tasks for scikit-learn☆17Updated 8 years ago
- Content for the Model Interpretability Tutorial at Pycon US 2019☆41Updated 7 months ago
- PyDataLondonTutorial☆26Updated 8 years ago