Deep Learning / fast

Once a week...

... I send out a list of most interesting libraries and apps in the "Deep Learning" section to about 1100 subscribers.

Do you want it too?

Hint: Click ↑ Pushed to see the most recently updated apps and libraries or click Growing to repos being actively starred .
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fastai_notes 🌿
28 (+0) ⭐

My classnotes, experiments, reproducible notebooks from fast.ai Deep Learning Class (v2)

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easyDL 🌿
18 (+0) ⭐

Easy and fast deep learning

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146 (+0) ⭐

Modification of fast.ai deep learning course notebooks for usage with Keras 2 and Python 3.

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23 (+0) ⭐

Deep Learning Quick Reference, published by Packt

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caffe 🌿
29416 (+6) ⭐

Caffe: a fast open framework for deep learning.

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fastai 🌿
16384 (+19) ⭐

The fastai deep learning library, plus lessons and tutorials

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FastPhotoStyle 🌿
9945 (+3) ⭐

Style transfer, deep learning, feature transform

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532 (+1) ⭐

An evolving guide to learning Deep Learning effectively.

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10 (+0) ⭐

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.

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68 (+0) ⭐

Deliberate Practice for Learning Deep Learning

10593 Deep Learning libraries
(18750 libraries)
Go
(86741 libraries)
(47493 libraries)
(14569 libraries)
(27612 libraries)
C#
(41657 libraries)
(23386 libraries)
(42913 libraries)
(13611 libraries)
(9542 libraries)
(23538 libraries)
(15963 libraries)
(151534 libraries)
(14108 libraries)
Vue
(12419 libraries)
CSS
(70226 libraries)
(59486 libraries)
(53317 libraries)
(10593 libraries)
C++
(89999 libraries)
C
(75410 libraries)
(43941 libraries)
(34384 libraries)
(10731 libraries)
(63915 libraries)
PHP
(95418 libraries)
(116711 libraries)
(114462 libraries)
(6015 libraries)
Nim
(3702 libraries)
D
(10799 libraries)
(38975 libraries)
(2405 libraries)