Deep-Learning-Book

Deep Learning book the covers the principles of deep learning, motivation, explanations, state of the art papers for the various tasks and architectures: CNNs, object detection, semantic segmentation, generative models, denoising, super resolution, style transfer and style manipulation, inpaintig, self supervised learning, vision transformers, OCR, and multi modal. Hope that it will be useful to some of you 🙂

neural-network book

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106 Stars

19 Forks

106 Watchers

Cost to Build

$1.05M

Market Value

$2.65M

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Growth over time

7 data points · 2022-02-01 → 2025-07-01

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What is the shellysheynin/Deep-Learning-Book GitHub project? Description: "Deep Learning book the covers the principles of deep learning, motivation, explanations, state of the art papers for the various tasks and architectures: CNNs, object detection, semantic segmentation, generative models, denoising, super resolution, style transfer and style manipulation, inpaintig, self supervised learning, vision transformers, OCR, and multi modal. Hope that it will be useful to some of you 🙂". Explain what it does, its main use cases, key features, and who would benefit from using it.

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