pythonfix
autoviz 0.1.808
Automatically Visualize any dataset, any size with a single line of code
Automatically Visualize any dataset, any size with a single line of code
Stars: 1617, Watchers: 1617, Forks: 195, Open Issues: 4The AutoViML/AutoViz repo was created 4 years ago and the last code push was 1 weeks ago.
The project is very popular with an impressive 1617 github stars!
How to Install autoviz
You can install autoviz using pip
pip install autoviz
or add it to a project with poetry
poetry add autoviz
Package Details
- Author
- Ram Seshadri
- License
- Apache License 2.0
- Homepage
- https://github.com/AutoViML/AutoViz.git
- PyPi:
- https://pypi.org/project/autoviz/
- GitHub Repo:
- https://github.com/AutoViML/AutoViz
Classifiers
Related Packages
Errors
A list of common autoviz errors.
Code Examples
Here are some autoviz code examples and snippets.
GitHub Issues
The autoviz package has 4 open issues on GitHub
- lightgbm instead of xgboost
Related Packages & Articles
dtreeviz 2.2.2
A Python 3 library for sci-kit learn, XGBoost, LightGBM, Spark, and TensorFlow decision tree visualization
autogluon.core 1.0.0
AutoML for Image, Text, and Tabular Data
open3d 0.18.0
Open3D: A Modern Library for 3D Data Processing.
onnxmltools 1.12.0
Converts Machine Learning models to ONNX
onnx 1.16.0
Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).
mne 1.6.1
MNE-Python project for MEG and EEG data analysis.
keras-tuner 1.4.7
A Hyperparameter Tuning Library for Keras
h2o 3.46.0.1
H2O, Fast Scalable Machine Learning, for python
dowhy 0.11.1
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions