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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Nilearn provides statistical and machine-learning tools for analyses of brain volumes and surfaces, with documentation and a community. It supports general linear model based analysis and uses the scikit-learn toolbox for multivariate statistics, with applications such as predictive modeling, classification, decoding and connectivity analysis. It is written in Python and installable with pip.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
nngraph is an open source GitHub repository that provides graph computation capabilities for Torch's nn neural network package. It enables users to define and work with neural network graph structures for their machine learning projects.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Notebooks is a Docker-based starter kit for machine learning through Jupyter notebooks, intended for users who want a ready runtime environment. Its images cover combinations of Keras, TensorFlow and PyTorch with CUDA v8 through v11, and include JupyterLab, scikit-learn, pandas and visualization, vision and NLP libraries. Python 3 only, as Python 2 is end-of-life.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Okrolearn is a machine learning library created in Python by Okerew. It provides a Tensor type and can be installed from PyPI for CPU or GPU use. The repository was archived by its owner on Sep 14, 2025, and is now read-only.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, specialized for real-time large scale machine learning. It is a framework for building applications and includes packaged end-to-end applications for collaborative filtering, classification, regression and clustering. The repository was archived by the owner on May 3, 2022, and is read-only.
github.com
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
github.com
Parris, the automated infrastructure setup tool for machine learning algorithms.
github.com
Pattern is a web mining module for Python with tools for data mining, natural language processing, machine learning, and network analysis and visualization. The repository is archived and no longer maintained, receiving no further updates, bug fixes or security patches.
github.com
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks. Materials are organized into sections covering preprocessing, model evaluation, parameter estimation, algorithms, clustering and data visualization.
github.com
Pattern Recognition Toolbox (PRT) is a free, MIT-licensed, object-oriented toolbox for machine learning and pattern recognition in MATLAB. It provides MATLAB commands and data types to help organize, visualize, process, cluster and classify data, and supports predictions based on data.
github.com
Petastorm is a library developed by Uber for deep learning model training and evaluation. It supports single-machine and distributed workflows with datasets in Apache Parquet format, is compatible with TensorFlow, PyTorch, and PySpark, and can be used via pure Python code.