Machinelearning Python Packages

clearml

ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

tslearn

The machine learning toolkit for time series analysis in Python

hydra-zen

Create powerful Hydra applications without the yaml files and boilerplate code.

nudenet

Lightweight nudity detection

netron

Visualizer for neural network, deep learning and machine learning models

covalent

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

raiutils

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

efficient-apriori

An efficient Python implementation of the Apriori algorithm.

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

nannyml

nannyml: post-deployment data science in python

colloq

Self-hosted classroom for teaching Python, data science and ML together. Students join from a browser with just a name

erroranalysis

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

dagshub

DagsHub client libraries

mllint

`mllint` is a command-line utility to evaluate the technical quality of Python Machine Learning (ML) projects by means of static analysis of the project's repository.

responsibleai

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

qai-hub-models-cli

Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.

a2ml

Common API for all "second gen" AutoML APIs: Auger.AI, Google Cloud AutoML and Azure AutoML

qai-hub-models

Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.

raiwidgets

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

boostaroota

A fast xgboost feature selection algorithm

deepsparse

Sparsity-aware deep learning inference runtime for CPUs

ludwig

Low-code framework for building custom LLMs, neural networks, and other AI models

kallisto

Efficiently calculate 3D-features for quantitative structure-activity relationship approaches.

sparrow-parse

Structured data extraction, instruction calling and agentic workflows with ML, LLM and Vision LLM