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for who have a passion for -
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
4. #DataScience
5. #Neuroscience

6. #ResearchPapers

7. Related Courses and Ebooks
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[🛠Understand basics of Deep Learning from scratch🛠]

If you're willing to understand how neural networks work behind the scene and debug the back-propagation algorithm step by step by yourself, these slides should be a good starting point.

We will cover deep learning popular applications, the concept of the artificial neuron and how it relates to the biological one, the perceptron and the multi-layer one. We'll also dive in activation functions, loss functions and formalize the training of a neural net via the back-propagation algorithm.

In the last part, you'll learn how to code a fully functioning trainable neural network from scratch. In pure python code only, with no frameworks involved.

slides: https://ahmedbesbes.com/introduction-to-neural-networks-and-deep-learning-from-scratch.html
code: https://github.com/ahmedbesbes/Neural-Network-from-scratch

#deeplearning
A Probabilistic Representation of Deep Learning

Xinjie Lan, Kenneth E. Barner : https://arxiv.org/abs/1908.09772v1

#deeplearning #machinelearning #neuralnetwork
Hierarchical Text Classification with Reinforced Label Assignment

Mao et al.: https://arxiv.org/abs/1908.10419

#InformationRetrieval #MachineLearning #ReinforcementLearning
Learning to Discover Novel Visual Categories via Deep Transfer Clustering

Han et al.: https://arxiv.org/abs/1908.09884

#ArtificialIntelligence #DeepLearning #NeuralNetworks
The top 20 free online CS courses of all time, via Class Central

Full list: bit.ly/CC100MOOCs #learntocode #MondayMotivation
Learning to Learn with Probabilistic Task Embeddings
https://bair.berkeley.edu/blog/2019/06/10/pearl/
Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting. https://arxiv.org/abs/1908.10937
Saccader: Improving Accuracy of Hard Attention Models for Vision
Gamaleldin F. Elsayed, Simon Kornblith, Quoc V. Le : https://arxiv.org/abs/1908.07644
#ArtificialIntelligence #DeepLearning #MachineLearning
ACL 2019 Thoughts and Notes
By Vinit Ravishankar, Daniel Hershcovich; edited by Artur Kulmizev, Mostafa Abdou : https://supernlp.github.io/2019/08/16/acl-2019/
#naturallanguageprocessing #machinelearning #deeplearning
wish I could add Bengio too.
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