This series looks at practical applications of machine learning from a Linux perspective. We feature free and open source software.
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Tag: deep learning
Best Free and Open Source Alternatives to Apple Intelligence
Apple Intelligence is a personal intelligence system that offers powerful generative models. We recommend the best free and open source alternatives.
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Machine Learning in Linux: Simplexity – simple Perplexity AI desktop app
Simplexity is a cross-platform app that lets you get answers courtesy of the Perplexity AI project.
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Vosk – offline speech recognition toolkit
Vosk is an offline speech recognition toolkit. It enables speech recognition for 20+ languages and dialects
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Machine Learning in Linux: Final2x – enhance your images with super-resolution
Final2x is GUI software that uses sophisticated AI models to enhance images by guessing what the details could be.
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Machine Learning in Linux: ocrs – modern OCR engine
ocrs is a Rust library and CLI tool for extracting text from images, also known as OCR (Optical Character Recognition).
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Machine Learning in Linux: EasyOCR – OCR that reads natural scene text and dense text in documents
EasyOCR is a Python module for extracting text from images.
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Machine Learning in Linux: Surya – multilingual document OCR toolkit adds text recognition
Surya is billed as a multilingual document OCR toolkit. It’s written in Python and published under an open source license.
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fastai – simplifies training fast and accurate neural nets using modern best practices
fastai simplifies training fast and accurate neural nets using modern best practices.
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Elephas – distributed deep learning with Keras and Spark
Elephas brings deep learning with Keras to Spark. Elephas intends to keep the simplicity and high usability of Keras
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TFLearn – deep learning library featuring a higher-level API for TensorFlow
TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
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NeuPy – Python library for Artificial Neural Networks – Deep Learning
NeuPy supports many different types of Neural Networks from a simple perceptron to deep learning models.
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Microsoft Cognitive Toolkit (CNTK) – toolkit for distributed deep learning
The Microsoft Cognitive Toolkit is a unified deep learning toolkit that describes neural networks as a series of computational steps via a directed graph.
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Chainer – framework for neural networks
Chainer is a Python-based deep learning framework aiming at flexibility.
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Theano – numerical computation library for Python
Theano is a numerical Python library that allows you to define, optimize, and evaluate mathematical expressions.
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MXNet – scalable deep learning framework
Apache MXNet is a modern deep learning framework used to train, and deploy deep neural networks.
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Caffe – deep learning framework by BAIR
Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at UC Berkeley.
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Keras – high-level neural networks API, written in Python
Keras has stronger adoption in both the industry and the research community than any other deep learning framework except TensorFlow.
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PyTorch – deep learning framework for fast, flexible experimentation
PyTorch provides libraries for basic tensor manipulation on CPUs or GPUs, a built-in neural network library, model training utilities, and more.
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TensorFlow – open source machine learning framework
TensorFlow is by far the most popular machine learning library. It’s used by Google, OpenAI, NVIDIA, Intel, SAP, eBay, Airbus, Uber, Airbnb, Snap, Dropbox and startups alike.
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