zk403's Stars
shap/shap
A game theoretic approach to explain the output of any machine learning model.
amphibian-dev/toad
ESC Team's credit scorecard tools.
microsoft/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
scikit-learn-contrib/category_encoders
A library of sklearn compatible categorical variable encoders
scipy/scipy
SciPy library main repository
dmlc/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
matplotlib/matplotlib
matplotlib: plotting with Python
statsmodels/statsmodels
Statsmodels: statistical modeling and econometrics in Python
pandas-dev/pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
dask/fastparquet
python implementation of the parquet columnar file format.
numpy/numpy
The fundamental package for scientific computing with Python.
rasbt/mlxtend
A library of extension and helper modules for Python's data analysis and machine learning libraries.
kaushalshetty/FeatureSelectionGA
Feature Selection using Genetic Algorithm (DEAP Framework)
scikit-optimize/scikit-optimize
Sequential model-based optimization with a `scipy.optimize` interface
aerdem4/lofo-importance
Leave One Feature Out Importance
ing-bank/probatus
Validation (like Recursive Feature Elimination for SHAP) of (multiclass) classifiers & regressors and data used to develop them.
cerlymarco/shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
stanfordmlgroup/ngboost
Natural Gradient Boosting for Probabilistic Prediction
ray-project/tune-sklearn
A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
feature-engine/feature_engine
Feature engineering package with sklearn like functionality
AutoViML/featurewiz
Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.
scikit-learn-contrib/imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
hyperopt/hyperopt
Distributed Asynchronous Hyperparameter Optimization in Python
catboost/benchmarks
Comparison tools
catboost/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
scikit-learn/scikit-learn
scikit-learn: machine learning in Python
paulbrodersen/netgraph
Publication-quality network visualisations in python
rasgointelligence/feature-engineering-tutorials
Data Science Feature Engineering and Selection Tutorials
luliyucoordinate/Leetcode
Play Leetcode with different programming language
pwwang/python-varname
Dark magics about variable names in python