pythonfix
econml 0.15.0
This package contains several methods for calculating Conditional Average Treatment Effects
This package contains several methods for calculating Conditional Average Treatment Effects
Stars: 3523, Watchers: 3523, Forks: 675, Open Issues: 343The py-why/EconML repo was created 5 years ago and the last code push was 5 days ago.
The project is very popular with an impressive 3523 github stars!
How to Install econml
You can install econml using pip
pip install econml
or add it to a project with poetry
poetry add econml
Package Details
- Author
- PyWhy contributors
- License
- MIT
- Homepage
- PyPi:
- https://pypi.org/project/econml/
- Documentation:
- https://econml.azurewebsites.net/
- GitHub Repo:
- https://github.com/Microsoft/EconML
Classifiers
Related Packages
Errors
A list of common econml errors.
Code Examples
Here are some econml code examples and snippets.
GitHub Issues
The econml package has 343 open issues on GitHub
- Expected input dimension for outcome nuisance model in DML
- Model file extremely large, saved using pickle
- OrthoForest spend days working without result
- ImportError: numpy.core.multiarray failed to import when importing econ.dml
- Doubts about structural equation of DML
- AttributeError: 'CausalEstimate' object has no attribute '_estimator_object'
- Why do OrthoForest and MetaLearners have no score() or tune() methods?
- Using FLAML in tune() methods
- Can we compare performance of DML estimators to DR Estimators based on the output of score method?
- Question on notation for causal forest learners
- Consistent notation for learner APIs
- Propensity model in Domain Adoptation Learner
- Tree Interpreter
- Domain Adoptation Learner
- Enable newer versions of python
Related Packages & Articles
dowhy 0.11.1
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions
causalml 0.15.0
Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms
easyocr 1.7.1
End-to-End Multi-Lingual Optical Character Recognition (OCR) Solution
dtreeviz 2.2.2
A Python 3 library for sci-kit learn, XGBoost, LightGBM, Spark, and TensorFlow decision tree visualization
dm-haiku 0.0.12
Haiku is a library for building neural networks in JAX.
dlib 19.24.4
A toolkit for making real world machine learning and data analysis applications
deepspeed 0.14.0
DeepSpeed is a Python package developed by Microsoft that provides a deep learning optimization library designed to scale across multiple GPUs and servers. It is capable of training models with billions or even trillions of parameters, achieving excellent system throughput and efficiently scaling to thousands of GPUs.
DeepSpeed is particularly useful for training and inference of large language models, and it falls under the category of Machine Learning Frameworks and Libraries. It is designed to work with PyTorch and offers system innovations such as Zero Redundancy Optimizer (ZeRO), 3D parallelism, and model-parallelism to enable efficient training of large models.
datasets 2.18.0
HuggingFace community-driven open-source library of datasets
corextopic 1.1
Hierarchical and semi-supervised topic modeling with minimal domain knowledge through Anchored Correlation Explanation