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     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
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/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


randomjungle 2.1.0
Dependencies: boost@1.89.0 gsl@2.8 libxml2@2.14.6 zlib@1.3.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://www.imbs.uni-luebeck.de/forschung/software/details.html#c224
Licenses: GPL 3+
Build system: gnu
Synopsis: Implementation of the Random Forests machine learning method
Description:

Random Jungle is an implementation of Random Forests. It is supposed to analyse high dimensional data. In genetics, it can be used for analysing big Genome Wide Association (GWA) data. Random Forests is a powerful machine learning method. Most interesting features are variable selection, missing value imputation, classifier creation, generalization error estimation and sample proximities between pairs of cases.

openmm 8.3.1
Dependencies: python-wrapper@3.11.14
Propagated dependencies: python-numpy@1.26.4
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/openmm/openmm/
Licenses: Expat
Build system: cmake
Synopsis: Toolkit for molecular simulation
Description:

OpenMM is a toolkit for molecular simulation. It can be used either as a stand-alone application for running simulations, or as a library you call from your own code.

python-faster-whisper 1.2.0
Propagated dependencies: onnxruntime@1.22.0 python-av@16.0.1 python-ctranslate2@4.6.0 python-huggingface-hub@0.31.4 python-tokenizers@0.19.1 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/SYSTRAN/faster-whisper
Licenses: Expat
Build system: pyproject
Synopsis: Whisper transcription reimplementation
Description:

This package provides a reimplementation of OpenAI's Whisper model using CTranslate2, which is a inference engine for transformer models.

python-tensorly 0.9.0
Propagated dependencies: python-jsmin@3.0.1 python-numpy@1.26.4 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/tensorly/tensorly
Licenses: Modified BSD
Build system: pyproject
Synopsis: Tensor learning in Python
Description:

This is a Python library that aims at making tensor learning simple and accessible. It allows performing tensor decomposition, tensor learning and tensor algebra easily. Its backend system allows seamlessly perform computation with NumPy, PyTorch, JAX, MXNet, TensorFlow or CuPy and run methodxs at scale on CPU or GPU.

python-readchar 4.2.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/magmax/python-readchar
Licenses: Expat
Build system: pyproject
Synopsis: Library to easily read single chars and key strokes
Description:

This package provides a Python library to easily read single characters and key strokes.

python-jaxtyping 0.3.3
Propagated dependencies: python-numpy@1.26.4 python-typeguard@4.4.4 python-typing-extensions@4.15.0 python-wadler-lindig@0.1.7
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/google/jaxtyping
Licenses: Expat
Build system: pyproject
Synopsis: Type annotations and runtime checking for JAX arrays and others
Description:

jaxtyping provides type annotations and runtime checking for shape and dtype of JAX arrays, PyTorch, NumPy, TensorFlow, and PyTrees.

python-scikit-learn 1.6.1
Dependencies: openblas@0.3.30
Propagated dependencies: python-joblib@1.5.2 python-numpy@1.26.4 python-scipy@1.12.0 python-threadpoolctl@3.1.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://scikit-learn.org/
Licenses: Modified BSD
Build system: pyproject
Synopsis: Machine Learning in Python
Description:

Scikit-learn provides simple and efficient tools for data mining and data analysis.

python-lightning-cloud 0.5.70
Propagated dependencies: python-boto3@1.40.61 python-click@8.1.8 python-fastapi@0.115.6 python-multipart@0.0.20 python-protobuf@3.20.3 python-pyjwt@2.10.1 python-requests@2.32.5 python-rich@13.7.1 python-six@1.17.0 python-urllib3@2.5.0 python-uvicorn@0.34.0 python-websocket-client@1.8.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://lightning.ai
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Lightning Cloud command line client
Description:

This package provides a command line interface for Lightning AI services.

python-gpytorch 1.14.2
Propagated dependencies: python-jaxtyping@0.3.3 python-linear-operator@0.6 python-mpmath@1.3.0 python-scikit-learn@1.7.0 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://gpytorch.ai
Licenses: Expat
Build system: pyproject
Synopsis: Implementation of Gaussian Processes in PyTorch
Description:

GPyTorch is a Gaussian process library implemented using PyTorch.

python-opentsne 1.0.2
Dependencies: fftw@3.3.10
Propagated dependencies: python-numpy@1.26.4 python-pynndescent@0.5.13 python-scikit-learn@1.7.0 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/pavlin-policar/openTSNE
Licenses: Modified BSD
Build system: pyproject
Synopsis: Extensible, parallel implementations of t-SNE
Description:

This is a modular Python implementation of t-Distributed Stochastic Neighbor Embedding (t-SNE), a popular dimensionality-reduction algorithm for visualizing high-dimensional data sets.

gloo 0.0.0-2.81925d1
Dependencies: openssl@1.1.1u rdma-core@60.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/facebookincubator/gloo
Licenses: Modified BSD
Build system: cmake
Synopsis: Collective communications library
Description:

Gloo is a collective communications library. It comes with a number of collective algorithms useful for machine learning applications. These include a barrier, broadcast, and allreduce.

python-ml-collections 1.1.0
Propagated dependencies: python-absl-py@2.3.1 python-pyyaml@6.0.2
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/google/ml_collections
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Python collections designed for Machine Learning usecases
Description:

ML Collections is a library of Python collections designed for Machine Learning usecases.

nerd-dictation 0-2.03ce043
Propagated dependencies: python-vosk@0.3.50
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/ideasman42/nerd-dictation
Licenses: GPL 2+
Build system: pyproject
Synopsis: Offline speech-to-text for desktop Linux
Description:

This package provides simple access speech to text for using in Linux without being tied to a desktop environment, using the vosk-api. The user configuration lets you manipulate text using Python string operations. It has zero overhead, as this relies on manual activation and there are no background processes. Dictation is accessed manually with nerd-dictation begin and nerd-dictation end commands.

python-hdbscan 0.8.40
Propagated dependencies: python-joblib@1.5.2 python-numpy@1.26.4 python-scikit-learn@1.7.0 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/scikit-learn-contrib/hdbscan
Licenses: Modified BSD
Build system: pyproject
Synopsis: High performance implementation of HDBSCAN clustering
Description:

HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates the result to find a clustering that gives the best stability over epsilon. This allows HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more robust to parameter selection. HDBSCAN is ideal for exploratory data analysis; it's a fast and robust algorithm that you can trust to return meaningful clusters (if there are any).

python-scikit-learn 1.7.0
Dependencies: openblas@0.3.30
Propagated dependencies: python-joblib@1.5.2 python-numpy@1.26.4 python-scipy@1.12.0 python-threadpoolctl@3.1.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://scikit-learn.org/
Licenses: Modified BSD
Build system: pyproject
Synopsis: Machine Learning in Python
Description:

Scikit-learn provides simple and efficient tools for data mining and data analysis.

tflite-micro 0-0.a94423c
Dependencies: flatbuffers@23.5.26 gemmlowp@0.1-2.16e8662 kissfft-for-tflite-micro@130 ruy@0-1.caa2443
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://ai.google.dev/edge/litert/microcontrollers/overview
Licenses: ASL 2.0
Build system: gnu
Synopsis: Infrastructure to enable deployment of ML models to embedded targets
Description:

TensorFlow Lite for Microcontrollers is a port of TensorFlow Lite designed to run machine learning models on DSPs, microcontrollers and other devices with limited memory.

llama-cpp 0.0.0-b7126
Dependencies: curl@8.6.0 glslang@1.4.321.0 python-gguf@0.17.1 python-minimal@3.11.14 openblas@0.3.30 spirv-headers@1.4.321.0 spirv-tools@1.4.321.0 vulkan-headers@1.4.321.0 vulkan-loader@1.4.321.0
Propagated dependencies: python-numpy@1.26.4 python-pytorch@2.9.0 python-sentencepiece@0.2.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/ggml-org/llama.cpp
Licenses: Expat
Build system: cmake
Synopsis: Port of Facebook's LLaMA model in C/C++
Description:

This package provides a port to Facebook's LLaMA collection of foundation language models. It requires models parameters to be downloaded independently to be able to run a LLaMA model.

python-lap 0.5.12
Propagated dependencies: python-numpy@1.26.4
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/gatagat/lap
Licenses: FreeBSD
Build system: pyproject
Synopsis: Linear Assignment Problem solver (LAPJV/LAPMOD)
Description:

Lap is a linear assignment problem solver using Jonker-Volgenant algorithm for dense (LAPJV) or sparse (LAPMOD) matrices.

nerd-dictation-sox-xdotool 0-2.03ce043
Dependencies: bash-minimal@5.2.37 nerd-dictation@0-2.03ce043
Propagated dependencies: sox@14.4.2 xdotool@3.20211022.1
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/ideasman42/nerd-dictation
Licenses: GPL 2+
Build system: trivial
Synopsis: Offline speech-to-text for desktop Linux
Description:

This package provides simple access speech to text for using in Linux without being tied to a desktop environment, using the vosk-api. The user configuration lets you manipulate text using Python string operations. It has zero overhead, as this relies on manual activation and there are no background processes. Dictation is accessed manually with nerd-dictation begin and nerd-dictation end commands.

python-brian2 2.5.1
Propagated dependencies: python-cython@3.1.2 python-jinja2@3.1.2 python-numpy@1.26.4 python-py-cpuinfo@9.0.0 python-pyparsing@3.2.3 python-setuptools@80.9.0 python-sympy@1.13.3
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://briansimulator.org/
Licenses: CeCILL
Build system: pyproject
Synopsis: Clock-driven simulator for spiking neural networks
Description:

Brian is a simulator for spiking neural networks written in Python. It is therefore designed to be easy to learn and use, highly flexible and easily extensible.

dmlc-core 0.5
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/dmlc/dmlc-core
Licenses: ASL 2.0
Build system: cmake
Synopsis: Common bricks library for machine learning
Description:

DMLC-Core is the backbone library to support all DMLC projects, offers the bricks to build efficient and scalable distributed machine learning libraries.

fasttext 0.9.2
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/facebookresearch/fastText
Licenses: Expat
Build system: cmake
Synopsis: Library for fast text representation and classification
Description:

fastText is a library for efficient learning of word representations and sentence classification.

python-hopcroftkarp 1.2.5-1.2846e1d
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://github.com/sofiatolaosebikan/hopcroftkarp
Licenses: GPL 3
Build system: pyproject
Synopsis: Implementation of the Hopcroft-Karp algorithm
Description:

This package implements the Hopcroft-Karp algorithm, producing a maximum cardinality matching from a bipartite graph.

python-xgboost 1.7.6
Dependencies: xgboost@1.7.6
Propagated dependencies: python-numpy@1.26.4 python-scipy@1.12.0
Channel: guix
Location: gnu/packages/machine-learning.scm (gnu packages machine-learning)
Home page: https://xgboost.ai/
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Python interface for the XGBoost library
Description:

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way.

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