Scikit Learn
Showing 36 of 42 projects
A 12-week, 26-lesson curriculum teaching classic machine learning using Scikit-learn through hands-on projects and quizzes.
A comprehensive guide to Python's essential data science libraries, available as free Jupyter notebooks.
A comprehensive collection of data science Python notebooks covering deep learning, machine learning, big data, visualization, and essential tools.
Jupyter notebooks with example code and exercises from the first edition of Hands-on Machine Learning with Scikit-Learn and TensorFlow.
An open standard format for representing machine learning models to enable interoperability between frameworks.
A cross-platform, high-performance accelerator for machine learning inference and training with ONNX models.
A Python library that explains predictions of any machine learning classifier using local interpretable model-agnostic explanations.
A curated guide to learning machine learning with Python and Jupyter Notebook, featuring hands-on tutorials, courses, and ethical considerations.
A curated guide to learning machine learning with Python and Jupyter Notebook, featuring courses, notebooks, and practical resources.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
An open-source, low-code Python library that automates end-to-end machine learning workflows.
A unified Python framework for machine learning with time series, offering scikit-learn compatible tools for forecasting, classification, clustering, and more.
A unified Python framework for machine learning with time series, offering scikit-learn compatible tools for forecasting, classification, clustering, and more.
An automated machine learning toolkit that serves as a drop-in replacement for scikit-learn estimators.
Code and Jupyter notebooks for the book 'Introduction to Machine Learning with Python' by Andreas Mueller and Sarah Guido.
An open-source Python library for automated feature engineering using Deep Feature Synthesis.
An open-source Python library for automated feature engineering using Deep Feature Synthesis.
An open-source Python package for training interpretable glassbox models and explaining blackbox machine learning systems.
A curated collection of Python tutorials and resources for data science, machine learning, and natural language processing.
Code repository for the 'Machine Learning with PyTorch and Scikit-Learn' book, providing practical examples and notebooks.
A modular container build system providing the latest AI/ML packages for NVIDIA Jetson and JetPack-L4T.
A suite of visual diagnostic tools that extend scikit-learn to steer machine learning model selection through visualizations.
A comprehensive collection of tutorials, examples, and resources for understanding and solving machine learning and pattern classification problems.
A collection of Jupyter notebooks accompanying a 10-part video series teaching machine learning with Python's scikit-learn library.
Seamlessly integrate large language models like ChatGPT into scikit-learn for enhanced text analysis tasks.
A curated list of Python software for data science, covering machine learning, deep learning, visualization, and data manipulation.
An Automated Machine Learning Python package for tabular data with feature engineering, hyperparameter tuning, explanations, and automatic documentation.
Transpile trained machine learning models into native code (Java, C, Python, Go, etc.) with zero dependencies.
HyperLearn provides 2-2000x faster machine learning algorithms with 50% less memory usage, optimized for all hardware.
An intuitive Python library that adds single-line plotting functions for scikit-learn and other machine learning objects.
A modular active learning framework for Python built on scikit-learn, enabling rapid creation of custom workflows.
A modular active learning framework for Python built on scikit-learn, enabling rapid creation of custom workflows.
A Python library for feature engineering and selection with scikit-learn compatible transformers.
Automatically visualize any dataset with a single line of code, including data quality assessment and fixes.
A Python library for probabilistic prediction using natural gradient boosting, built on scikit-learn.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.