Fast and Accurate ML in 3 Lines of Code
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A unified framework for machine learning with time series
- time-series
- machine-learning
- scikit-learn
- time-series-classification
An open source python library for automated feature engineering
- feature-engineering
- machine-learning
- data-science
- automated-machine-learning
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
A scikit-learn compatible neural network library that wraps PyTorch
Visual analysis and diagnostic tools to facilitate machine learning model selection.
- machine-learning
- visual-analysis
- model-selection
- visualization
🛠 All-in-one web-based IDE specialized for machine learning and data science.
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
- machine-learning
- scikit-learn
- statistical-learning
- xgboost
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Pandas integration with sklearn
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
An intuitive library to add plotting functionality to scikit-learn objects.
Feature engineering and selection open-source Python library compatible with sklearn.
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
- visualization
- python3
- python
- xgboost
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
- forecasting
- scikit-learn
- machine-learning
- python
Transpile trained scikit-learn estimators and transformers to C, C#, Go, Java, JavaScript, PHP and Ruby.
Use evolutionary algorithms instead of gridsearch in scikit-learn
Python package for Bayesian Machine Learning with scikit-learn API
- python
- bayesian-machine-learning
- machine-learning
- scikit-learn
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
- feature-selection
- data-science
- python
Python for chemoinformatics
- chemoinformatics
- scikit-learn
- cheminformatics
- python
scikit-learn wrappers for Python fastText.
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.
- feature-engineering
- transformers
- pre-processing
- data-science
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.