Education
133 items from guillaume-chevalier/awesome-deep-learning-resources ★1,821
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Keras keras.io
A high-level neural networks API running on top of TensorFlow.
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SQuAD1.0 rajpurkar.github.io
Question answering dataset that can be explored online, and a list of models performing well on that dataset.
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The Unreasonable effectiveness of RNNs karpathy.github.io
, Torch Code, Python Code
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Machine Learning Course by Andrew Ng (Stanford University) coursera.org
Renown entry-level online class with certificate. Taught by: Andrew Ng, Associate Professor, Stanford University; Chief Scientist, Baidu; Chairman and Co-founder, Coursera.
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Deep Learning deeplearningbook.org
Yet halfway through the book, it contains satisfying math content on how to think about actual deep learning.
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Migrating to Git LFS for Developing Deep Learning Applications with Large Files vooban.com
Easily manage huge files in your private Git projects.
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Deep Residual Learning for Image Recognition arxiv.org
Very deep residual layers with batch normalization layers - a.k.a. "how to overfit any vision dataset with too many layers and make any vision model work properly at recognition given enough data".
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Attention Is All You Need arxiv.org
(AIAYN) - Introducing multi-head self-attention neural networks with positional encoding to do sentence-level NLP without any RNN nor CNN - this paper is a must-read (also see this explanation and this visualization of the paper).
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Arxiv Sanity Preserver arxiv-sanity.com
arXiv browser with TF/IDF features.
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Hyperopt tutorial for Optimizing Neural Networks’ Hyperparameters vooban.com
Learn to slay down hyperparameter spaces automatically rather than by hand.
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Discover structure behind data with decision trees vooban.com
Grow and plot a decision tree to automatically figure out hidden rules in your data
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Understanding LSTM Networks colah.github.io
Explains the LSTM cells' inner workings, plus, it has interesting links in conclusion.
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Neural Networks video series by Hugo Larochelle youtube.com
Interesting class about neural networks available online for free by Hugo Larochelle, yet I have watched a few of those videos.
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Coursera Deep Learning Specialization coursera.org
New series of 5 Deep Learning courses by Andrew Ng, now with Python rather than Matlab/Octave, and which leads to a specialization certificate.
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Two Minute Papers' Channel youtube.com
Interesting and shallow overview of some research papers, for example about WaveNet or Neural Style Transfer.
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Computer Science youtube.com
Yet another YouTube playlist I composed, this time about various CS topics.
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Signal Processing Playlist youtube.com
A YouTube playlist I composed about DFT/FFT, STFT and the Laplace transform - I was mad about my software engineering bachelor not including signal processing classes (except a bit in the quantum physics class).
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Deep Learning & Machine Learning (Advanced topics) youtube.com
A list of videos about deep learning that I found interesting or useful, this is a mix of a bit of everything.
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Tensor Calculus and the Calculus of Moving Surfaces youtube.com
Generalize properly how Tensors work, yet just watching a few videos already helps a lot to grasp the concepts.
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Siraj's Channel youtube.com
Siraj has entertaining, fast-paced video tutorials about deep learning.
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What is the Best Multi-Stage Architecture for Object Recognition? yann.lecun.com
Awesome for the use of "local contrast normalization".
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Neuralink and the Brain’s Magical Future waitbutwhy.com
Thought provoking article about the future of the brain and brain-computer interfaces.
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Why do 87% of data science projects never make it into production? venturebeat.com
Data is not to be overlooked, and communication between teams and data scientists is important to integrate solutions properly.
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SOLID Machine Learning umaneo.com
The SOLID principles applied to Machine Learning.
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GLO-4030/7030 Apprentissage par réseaux de neurones profonds ulaval-damas.github.io
This is a class given by Philippe Giguère, Professor at University Laval. I especially found awesome its rare visualization of the multi-head attention mechanism, which can be contemplated at the slide 28 of week 13's class.
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Machine Learning for Trading by Georgia Tech udacity.com
Interesting class for acquiring basic knowledge of machine learning applied to trading and some AI and finance concepts. I especially liked the section on Q-Learning.
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Deep Learning by Google udacity.com
Good intermediate to advanced-level course covering high-level deep learning concepts, I found it helps to get creative once the basics are acquired.
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François Chollet's Twitter twitter.com
Author of Keras - has interesting Twitter posts and innovative ideas.
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The real reason most ML projects fail towardsdatascience.com
Focus on clear business objectives, avoid pivots of algorithms unless you have really clean code, and be able to know when what you coded is "good enough".
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NLP's ImageNet moment has arrived thegradient.pub
All hail NLP's ImageNet moment.
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