Showing 1-16 of 16 projects
A high-performance gradient boosting framework for machine learning tasks like ranking, classification, and more.
SynapseML is a simple and distributed machine learning library for building and deploying AI models at scale.
An AutoML Python package for tabular data with feature engineering, hyperparameter tuning, and automatic documentation.
Transform ML models into native code (Java, C, Python, Go, etc.) with zero dependencies
A Python library for inspecting and explaining machine learning models and their predictions.
A unified framework for large-scale data computation that scales popular Python data tools like NumPy, Pandas, and Scikit-Learn.
A distributed machine learning toolkit from Microsoft for building scalable AI and ML models.
A curated collection of research papers on decision, classification and regression trees with implementations.
Automated machine learning for analytics & production use cases powered by popular ML libraries.
MLBox is a powerful automated machine learning Python library that simplifies and accelerates the machine learning workflow.
A comprehensive Python library for time series forecasting using machine learning models.
A scalable Python library for data science and machine learning tasks with API compatibility and lightning-fast performance.
Automated Deep Learning without any human intervention, the first solution for the AutoDL challenge@NeurIPS.
A scalable machine learning library for time series forecasting in Python.
A collection of pre-compiled packages for AWS Lambda, useful for AI/ML and other serverless workloads.
A curated list of gradient boosting research papers with implementations in Python.
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