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> ML_LIBRARIES_CATALOG_v1.0

Qualified ML Libraries

Every library is independently qualified with primary citations, supported version ranges, hardware accelerator separation, and real-world failure patterns.

Showing 17 of 161 Qualified Libraries & Tools (Page 9 of 9)Accelerator Mappings & Failure Modes
client-edge-embedded
2.9.0Apache-2.0

MNN (Mobile Neural Network)

Alibaba Group

Alibaba's lightweight, high-performance deep learning framework for mobile and embedded devices.

Training:
CPUCUDA
Inference:
CPUCUDAWASM
#image#video#text
client-edge-embedded
8.0BSD-3-Clause

coremltools

Apple Inc.

Apple's official toolkit for converting, compressing, and optimizing models for the Apple Neural Engine.

Training:
Not Supported (Inference Only)
Inference:
CPUMPS
#image#text#audio#tabular
non-python-ecosystems
1.2.0MIT

tidymodels (R)

Posit Software (formerly RStudio)

Posit's modern machine learning framework for the R ecosystem using Tidyverse principles.

Training:
CPU
Inference:
CPU
#tabular
non-python-ecosystems
6.0-94GPL-2.0

caret (R)

Max Kuhn / R Community

The classic Classification and REgression Training package that defined machine learning in R.

Training:
CPU
Inference:
CPU
#tabular
non-python-ecosystems
0.21.0LGPL-3.0

mlr3 (R)

mlr-org / LMU Munich / TU Dortmund

Next-generation object-oriented machine learning framework for R built on R6 and data.table.

Training:
CPU
Inference:
CPU
#tabular
non-python-ecosystems
3.8.6GPL-3.0

Weka

University of Waikato

The classic Java data mining and machine learning workbench from the University of Waikato.

Training:
CPU
Inference:
CPU
#tabular
non-python-ecosystems
3.0.2Apache-2.0

Smile (JVM)

Haifeng Li / Smile Project

High-performance statistical machine learning and linear algebra engine for Java and Scala.

Training:
CPU
Inference:
CPU
#tabular#text
non-python-ecosystems
4.3.1Apache-2.0

Tribuo

Oracle Labs

Oracle Labs' type-safe machine learning library for Java with automated provenance tracking.

Training:
CPU
Inference:
CPUCUDA
#tabular#text
non-python-ecosystems
0.29.0Apache-2.0

Deep Java Library (DJL)

Amazon Web Services (AWS)

AWS's engine-agnostic deep learning framework for Java, Scala, and Kotlin.

Training:
CPUCUDA
Inference:
CPUCUDA
#text#image#audio#tabular
non-python-ecosystems
1.0.0-M2.1Apache-2.0

Eclipse Deeplearning4j (DL4J)

Eclipse Foundation / Konduit

Eclipse Foundation's distributed deep learning suite for the Java Virtual Machine and Apache Spark.

Training:
CPUCUDA
Inference:
CPUCUDA
#tabular#image#text
non-python-ecosystems
3.0.1MIT

ML.NET

Microsoft / .NET Foundation

Microsoft's open-source, cross-platform machine learning framework for .NET developers.

Training:
CPUCUDA
Inference:
CPUCUDAWASM
#tabular#text#image
non-python-ecosystems
0.103.0MIT

TorchSharp

.NET Foundation / Microsoft

.NET Foundation's official C# bindings to PyTorch LibTorch for GPU-accelerated deep learning.

Training:
CPUCUDA
Inference:
CPUCUDA
#tabular#image#text#audio
non-python-ecosystems
0.7.0Apache-2.0 OR MIT

Linfa (Rust)

Rust ML Working Group

A comprehensive, memory-safe classical machine learning library for the Rust ecosystem.

Training:
CPU
Inference:
CPUWASM
#tabular
non-python-ecosystems
0.6.0Apache-2.0 OR MIT

Candle (Rust)

Hugging Face

Hugging Face's minimalist, high-performance deep learning framework for Rust with WebGPU and CUDA.

Training:
CPUCUDAMPS
Inference:
CPUCUDAMPSWEBGPUWASM
#text#audio#image
non-python-ecosystems
0.14.0Apache-2.0 OR MIT

Burn (Rust)

Tracel AI / Burn Community

A comprehensive, flexible, and high-performance deep learning framework in pure Rust.

Training:
CPUCUDAROCMMPSXPU
Inference:
CPUCUDAROCMMPSWEBGPUWASM
#tabular#image#text#audio
non-python-ecosystems
0.14.16MIT

Flux.jl (Julia)

JuliaLang / FluxML Community

The premier deep learning and differentiable programming framework for the Julia language.

Training:
CPUCUDAROCMMPS
Inference:
CPUCUDAROCMMPS
#tabular#image#time-series
non-python-ecosystems
0.20.5MIT

MLJ.jl (Julia)

Alan Turing Institute / JuliaAI

The Alan Turing Institute's machine learning framework for Julia with scientific type safety.

Training:
CPU
Inference:
CPU
#tabular