Machine Learning
Showing 36 of 1845 projects
Hyperopt-sklearn automates hyperparameter optimization and model selection for scikit-learn machine learning pipelines.
A multi-language library providing implementations of common supervised machine learning evaluation metrics.
A Python package for generating synthetic tabular and time-series data using state-of-the-art generative models like GANs and Gaussian Mixtures.
Machine learning with dataframes
A Python library for automated hyperparameter optimization and model evaluation with TensorFlow, Keras, and PyTorch.
Python implementation of the Boruta all-relevant feature selection method with scikit-learn compatibility.
An all-in-one framework for training state-of-the-art computer vision models, covering pretraining, fine-tuning, and distillation.
A fast Support Vector Machine (SVM) library that leverages GPUs and multi-core CPUs for high-performance machine learning.
A curated collection of 60 ChatGPT prompts for data science tasks, from model building to code explanation.
A Go machine learning library with online learning capabilities and a variety of implemented models.
A Python package for concise, transparent, and accurate predictive modeling with sklearn-compatible interpretable models.
A deprecated repository for community-contributed Keras extensions like layers, activations, and loss functions.
Elephas is a Keras extension for distributed deep learning on Apache Spark, enabling data-parallel training at scale.
An open-source Python repository providing around 40 feature selection algorithms for machine learning applications.
A high-level Deep Learning API for JVM and Android developers, written in Kotlin and inspired by Keras.
A Python library that automatically extracts schema, statistics, and sensitive entities (PII/NPI) from datasets.
A Bayesian optimization software package for automatically running experiments to minimize an objective in as few runs as possible.
A Python framework for building real-time data pipelines and event-driven microservices on Apache Kafka using a Streaming DataFrame API.
A state-of-the-art diffusion model for predicting how small molecules (ligands) bind to proteins.
A machine learning framework for iOS that records location and motion data and detects user activity types like walking, cycling, and transport modes.
MLBox is a powerful Automated Machine Learning python library.
MLeap is a portable execution engine for deploying machine learning pipelines from Spark and Scikit-learn without their runtime dependencies.
A TensorFlow library for building Graph Neural Networks with support for heterogeneous graphs and scalable data processing.
A Python library for agile data preparation workflows that works with Pandas, Dask, cuDF, Dask-cuDF, Vaex, and PySpark.
A curated list of resources for Document Understanding (DU), covering research, datasets, tools, and applications in Intelligent Document Processing.
A curated collection of must-read academic papers on knowledge representation learning and knowledge embedding, with an associated open-source toolkit.
A Python library for time series forecasting using scikit-learn compatible machine learning models.
A Python library for time series forecasting using scikit-learn compatible machine learning models.
A comprehensive Python library for generating and analyzing multi-class confusion matrices with extensive statistical metrics.
A software implementation of factorization machines for estimating interactions between categorical variables in large datasets.
An accelerated machine learning framework for Go, offering a PyTorch/Jax/TensorFlow-like experience with support for CPUs, GPUs, TPUs, and WASM.
A Ruby library implementing the ID3 algorithm for decision tree learning with support for continuous and discrete datasets.
A C++-based high-performance parallel environment execution engine for vectorized reinforcement learning simulations.
A comprehensive benchmark suite for evaluating speed, throughput, and resource utilization of big data frameworks like Hadoop, Spark, and streaming engines.
Type annotations and runtime checking for PyTorch tensor shape, dtype, layout, and names.
A foundational PyTorch library for training deep learning models, serving as the core engine for the OpenMMLab ecosystem.
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