Rust Burn Library for Deep Learning
KDnuggets
OCTOBER 13, 2023
A new deep learning framework built entirely in Rust that aims to balance flexibility, performance, and ease of use for researchers, ML engineers, and developers.
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KDnuggets
OCTOBER 13, 2023
A new deep learning framework built entirely in Rust that aims to balance flexibility, performance, and ease of use for researchers, ML engineers, and developers.
Analytics Vidhya
JUNE 14, 2024
Introduction Efficient ML models and frameworks for building or even deploying are the need of the hour after the advent of Machine Learning (ML) and Artificial Intelligence (AI) in various sectors. Although there are several frameworks, PyTorch and TensorFlow emerge as the most famous and commonly used ones.
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PyTorch and TensorFlow are the two leading AI/ML Frameworks. In this article, we take a look at their on-device counterparts PyTorch Mobile and TensorFlow Lite and examine them more deeply from the perspective of someone who wishes to develop and deploy models for use on mobile platforms.
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Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. This is where visualizations in ML come in.
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Table of contents Overview Traditional Software development Life Cycle Waterfall Model Agile Model DevOps Challenges in ML models Understanding MLOps Data Engineering Machine Learning DevOps Endnotes Overview: MLOps According to research by deeplearning.ai, only 2% of the companies using Machine Learning, Deep learning have […].
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