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An open source Python library for drift detection in machine learning systems.
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Fundamentals of machine learning in python.
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Hyperopt is an open-source Python library available on GitHub, designed to provide distributed asynchronous hyperparameter optimization functionality for tuning machine learning models in development workflows, production environments, as well as research settings.
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Kubeflow Katib is a Kubernetes-native project for automated machine learning (AutoML). It supports hyperparameter tuning, early stopping and neural architecture search, and is agnostic to machine learning frameworks, natively supporting frameworks such as TensorFlow, PyTorch and XGBoost. Training jobs can use any Kubernetes Custom Resources, with out-of-box support for Kubeflow Training Operator, Argo Workflows and Tekton Pipelines. A Python SDK simplifies creating tuning jobs.
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LightlySSL is a Python computer vision framework for self-supervised learning on images, written in a PyTorch-like style. It exposes low-level building blocks such as loss functions and model heads, supports custom backbone models for self-supervised pre-training, and supports distributed training using PyTorch Lightning. Sample code covers models including MoCo, SimCLR, BYOL and DINO.
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MCGrad is a tool for multicalibration that aims to keep machine learning model predictions calibrated globally and across segments defined by features. It requires Python 3.10+ and is installed with pip or conda; the project's own description says it has been deployed at Meta on hundreds of production models.
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A minimal, educational, Pythonic implementation of autograd (~100 loc).
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MLBox is an open-source automated machine learning library implemented in Python, hosted in the AxeldeRomblay/MLBox GitHub repository. It provides contribution guidelines, project topic information, and resources documenting the library's functionality.
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Lightweight ML utility for automated training, evaluation, and prediction with CLI and Python API support.
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mljar-supervised is an Automated Machine Learning Python package for tabular data. It automates data preprocessing, model construction and hyperparameter tuning, and produces a Markdown report for each model. It offers Explain, Perform and Compete modes, along with model explanations and generated web apps for predictions.
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mlxtend is a library that provides extension and helper modules for Python's data analysis and machine learning libraries. The project includes installation guides, example code, license information, and contact details. It is hosted as an open source repository on GitHub.
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neonrvm is an open-source machine learning library for performing regression tasks using the Relevance Vector Machine (RVM) technique. It is written in Python and available on GitHub. The library aims to provide efficient implementations for RVM-based regression.
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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.
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OPFython is a GitHub repository offering a Python-inspired implementation of the Optimum-Path Forest classifier. The library enables classification tasks using the optimum-path forest algorithm. It includes installation instructions, quick start guides, and classifier documentation. The project is open source and welcomes contributions from the community.
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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.
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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.
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Hidden Markov Models for Python, implemented in Cython for speed and efficiency.
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Multidimensional cluster generation in Python.
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A Python library for secure and private Deep Learning built on PyTorch and TensorFlow.
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PyTorch is a Python package providing tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. It includes components such as torch, torch.autograd, torch.nn, and torch.utils, and can be used as a NumPy replacement or a deep learning research platform.
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PyVarInf is a Python package that facilitates the use of Bayesian deep learning methods with variational inference for PyTorch, providing facilities to train PyTorch neural network models using variational inference. It approximates the posterior distribution over network weights with a parametric distribution.
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Tutorial on Python time-series model deployment.
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Deep learning based facial detector for Python coming with facial landmarks.
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Better DeepSeek is an open-source browser extension that adds tools to the DeepSeek chat interface, including a customizable system prompt, persistent memory, and tag-based output. It can generate downloadable files, PowerPoint and Excel documents, and multi-file ZIP projects, and run Python in the browser. The project is described as unofficial and independent.