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Awesome Education

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier

Here you can see meta information about this topic like the time we last updated this page, the original creator of the awesome list and a link to the original GitHub repository.

Last Update: Aug. 7, 2022, 6:14 p.m.

Thank you guillaume-chevalier & contributors
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guillaume-chevalier/awesome-deep-learning-resources

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Online Classes

Books

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Librairies and Implementations

A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.

472
51
9m
Apache-2.0

An Open Source Machine Learning Framework for Everyone

166.87K
87.03K
4d
Apache-2.0

Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning

3.21K
469
11m
Apache-2.0

"Neural Turing Machine" in Tensorflow

1.02K
218
5y 83d
MIT

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

2.92K
872
1y 87d
MIT

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

264
90
2y 4m
Apache-2.0

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

966
288
11m
Apache-2.0

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

101
75
4y 95d
n/a

Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.

0
1
4y 11m
MIT

Attempt at reproducing a SGNN's projection layer, but with word n-grams instead of skip-grams. Paper and more: http://aclweb.org/anthology/D18-1105

22
2
3y 7m
BSD-3-Clause

A coding exercise: let's convert dirty machine learning code into clean code using a Pipeline - which is the Pipe and Filter Design Pattern applied to Machine Learning.

11
5
2y 76d
n/a

Some Datasets

Gradient Descent Algorithms & Optimization Theory

Complex Numbers & Digital Signal Processing

Recurrent Neural Networks

Convolutional Neural Networks

Attention Mechanisms

Other

YouTube and Videos

Misc. Hubs & Links