* [https://en.wikipedia.org/wiki/Neuron Neuron from Wikipedia]
* [https://en.wikipedia.org/wiki/Neural_pathway Neural pathway from Wikipedia]
'''==ANNs'''==
* [https://en.wikipedia.org/wiki/Artificial_neural_network Artificial neural network from Wikipedia]
* [https://en.wikipedia.org/wiki/Types_of_artificial_neural_networks Types of artificial neural networks from Wikipedia]
* [https://en.wikipedia.org/wiki/Helmholtz_machine Helmholtz machine from Wikipedia]
* [http://de.slideshare.net/piuprabhu/chess-end-games-using-neural-networks-presentation Chess end games using Neural Networks]
'''===Topics'''===
* [https://en.wikipedia.org/wiki/Artificial_neuron Artificial neuron from Wikipedia]
* [https://en.wikipedia.org/wiki/Connectionism Connectionism from Wikipedia]
* [https://en.wikipedia.org/wiki/Convolutional_neural_network Convolutional neural network from Wikipedia]
* [https://wiki.tum.de/display/lfdv/Convolutional+Neural+Networks+for+Image+and+Video+Processing Convolutional Neural Networks for Image and Video Processing], [https://wiki.tum.de/ TUM Wiki], [[Technical University of Munich]]
: [https://wiki.tum.de/display/lfdv/Convolutional+Neural+Networks#ConvolutionalNeuralNetworks-convolution Convolutional Neural Networks]
: [https://wiki.tum.de/display/lfdv/Deep+Residual+Networks Deep Residual Networks]
: [https://towardsdatascience.com/types-of-convolutions-in-deep-learning-717013397f4d An Introduction to different Types of Convolutions in Deep Learning] by [http://plpp.de/ Paul-Louis Pröve], July 22, 2017
: [https://towardsdatascience.com/squeeze-and-excitation-networks-9ef5e71eacd7 Squeeze-and-Excitation Networks] by [http://plpp.de/ Paul-Louis Pröve], October 17, 2017
* [https://en.wikipedia.org/wiki/Deep_learning Deep Learning from Wikipeadia]
* [http://www.scholarpedia.org/article/Deep_Learning Deep Learning - Scholarpedia] by [[Jürgen Schmidhuber]]
* [https://en.wikipedia.org/wiki/Spiking_neural_network Spiking neural network from Wikipedia]
* [https://en.wikipedia.org/wiki/Time_delay_neural_network Time delay neural network from Wikipedia]
'''===CNNs===* [https://en.wikipedia.org/wiki/Convolutional_neural_network Convolutional neural network from Wikipedia]* [https://wiki.tum.de/display/lfdv/Convolutional+Neural+Networks+for+Image+and+Video+Processing Convolutional Neural Networks for Image and Video Processing], [https://wiki.tum.de/ TUM Wiki], [[Technical University of Munich]]: [https://wiki.tum.de/display/lfdv/Convolutional+Neural+Networks#ConvolutionalNeuralNetworks-convolution Convolutional Neural Networks]: [https://wiki.tum.de/display/lfdv/Deep+Residual+Networks Deep Residual Networks]: [https://towardsdatascience.com/types-of-convolutions-in-deep-learning-717013397f4d An Introduction to different Types of Convolutions in Deep Learning] by [http://plpp.de/ Paul-Louis Pröve], July 22, 2017: [https://towardsdatascience.com/squeeze-and-excitation-networks-9ef5e71eacd7 Squeeze-and-Excitation Networks] by [http://plpp.de/ Paul-Louis Pröve], October 17, 2017===RNNs'''===
* [https://en.wikipedia.org/wiki/Recurrent_neural_network Recurrent neural network from Wikipedia]
* [http://www.scholarpedia.org/article/Recurrent_neural_networks Recurrent neural networks - Scholarpedia]
* [http://www.scholarpedia.org/article/Hopfield_network Hopfield network - Scholarpedia]
* [https://en.wikipedia.org/wiki/Long_short_term_memory Long short term memory from Wikipedia]
'''==Activation Functions'''==
* [https://en.wikipedia.org/wiki/Activation_function Activation function from Wikipedia]
* [https://en.wikipedia.org/wiki/Rectifier_(neural_networks) Rectifier (neural networks) from Wikipedia]
* [https://en.wikipedia.org/wiki/Sigmoid_function Sigmoid function from Wikipedia]
'''==Backpropagation'''==
* [https://en.wikipedia.org/wiki/Backpropagation Backpropagation from Wikipedia]
* [https://en.wikipedia.org/wiki/Backpropagation_through_structure Backpropagation through structure from Wikipedia]
* [https://en.wikipedia.org/wiki/Rprop Rprop from Wikipedia]
* [http://people.idsia.ch/~juergen/who-invented-backpropagation.html Who Invented Backpropagation?] by [[Jürgen Schmidhuber]] (2014, 2015)
'''==Gradient'''==
* [https://en.wikipedia.org/wiki/Gradient Gradient from Wikipedia]
* [https://en.wikipedia.org/wiki/Del Del from Wikipedia]
* [https://blogs.princeton.edu/imabandit/2014/03/06/nesterovs-accelerated-gradient-descent-for-smooth-and-strongly-convex-optimization/ Nesterov’s Accelerated Gradient Descent for Smooth and Strongly Convex Optimization] by [[Sébastien Bubeck]], [https://blogs.princeton.edu/imabandit/ I’m a bandit], March 6, 2014
* [https://blogs.princeton.edu/imabandit/2015/06/30/revisiting-nesterovs-acceleration/ Revisiting Nesterov’s Acceleration] by [[Sébastien Bubeck]], [https://blogs.princeton.edu/imabandit/ I’m a bandit], June 30, 2015
'''==Software==* [https://en.wikipedia.org/wiki/Neural_network_software Neural network software from Wikipedia]: [https://en.wikipedia.org/wiki/Neural_Lab Neural Lab from Wikipedia]: [https://en.wikipedia.org/wiki/SNNS SNNS from Wikipedia]* [https://en.wikipedia.org/wiki/Comparison_of_deep_learning_software Comparison of deep learning software from Wikipedia]==Libraries==* [https://en.wikipedia.org/wiki/Eigen_%28C%2B%2B_library%29 Eigen (C++ library) from Wikipedia]* [http://leenissen.dk/fann/wp/ Fast Artificial Neural Network Library (FANN)]* [https://wiki.python.org/moin/PythonForArtificialIntelligence PythonForArtificialIntelligence - Python Wiki] [[Python]]* [https://en.wikipedia.org/wiki/TensorFlow TensorFlow from Wikipedia]==Blogs'''==
* [https://theneural.wordpress.com/ Neural Networks Blog] by [[Ilya Sutskever]]
* [https://software.intel.com/en-us/articles/an-introduction-to-neural-networks-with-an-application-to-games An Introduction to Neural Networks with an Application to Games] by [https://www.linkedin.com/pub/dean-p-macri/a/762/68b Dean Macri], [https://en.wikipedia.org/wiki/Intel_Developer_Zone Intel Developer Zone], September 9, 2011
* [https://blog.waya.ai/deep-residual-learning-9610bb62c355 Understand Deep Residual Networks — a simple, modular learning framework that has redefined state-of-the-art] by [https://blog.waya.ai/@waya.ai Michael Dietz], [https://blog.waya.ai/ Waya.ai], May 02, 2017
* [https://medium.com/applied-data-science/how-to-build-your-own-alphazero-ai-using-python-and-keras-7f664945c188 How to build your own AlphaZero AI using Python and Keras] by [https://www.linkedin.com/in/davidtfoster/ David Foster], January 26, 2018 » [[AlphaZero]], [[Connect Four]], [[Python]]
'''Libraries'''* [https://en.wikipedia.org/wiki/Eigen_%28C%2B%2B_library%29 Eigen (C++ library) from Wikipedia]* [http://leenissen.dk/fann/wp/ Fast Artificial Neural Network Library (FANN)]* [https://wiki.python.org/moin/PythonForArtificialIntelligence PythonForArtificialIntelligence - Python Wiki] [[Python]]* [https://en.wikipedia.org/wiki/TensorFlow TensorFlow from Wikipedia]'''Software'''* [https://en.wikipedia.org/wiki/Neural_network_software Neural network software from Wikipedia]: [https://en.wikipedia.org/wiki/Neural_Lab Neural Lab from Wikipedia]: [https://en.wikipedia.org/wiki/SNNS SNNS from Wikipedia]* [https://en.wikipedia.org/wiki/Comparison_of_deep_learning_software Comparison of deep learning software from Wikipedia]'''==Courses'''==
* [http://www.cedar.buffalo.edu/~srihari/CSE574/index.html Machine Learning and Probabilistic Graphical Models: Course Materials - 5. Neural Networks] by [https://en.wikipedia.org/wiki/Sargur_Srihari Sargur Srihari], [https://en.wikipedia.org/wiki/University_at_Buffalo University at Buffalo]
* [http://www.holehouse.org/mlclass/08_Neural_Networks_Representation.html Neural Networks - Representation] from [http://www.holehouse.org/mlclass/index.html Stanford Machine Learning] by [[Andrew Ng]]
: [https://youtu.be/Ilg3gGewQ5U What is backpropagation really doing? | Chapter 3]
: [https://youtu.be/tIeHLnjs5U8 Backpropagation calculus | Appendix to Chapter 3]
'''* [[Mathematician#FFLi|Fei-Fei Li]], [[Mathematician#JustinJohnson|Justin Johnson]], [[Mathematician#SYeung|Serena Yeung]] - [http://cs231n.stanford.edu/ CS231n Convolutional Neural Networks for Visual Recognition], [[Stanford University]], [https://en.wikipedia.org/wiki/YouTube YouTube] Videos: [https://www.youtube.com/watch?v=vT1JzLTH4G4 Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture1.pdf slides]: [https://www.youtube.com/watch?v=OoUX-nOEjG0 Lecture 2 | Image Classification] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture2.pdf slides]: [https://www.youtube.com/watch?v=h7iBpEHGVNc Lecture 3 | Loss Functions and Optimization] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture3.pdf slides]: [https://www.youtube.com/watch?v=d14TUNcbn1k Lecture 4 | Introduction to Neural Networks] by [[Mathematician#SYeung|Serena Yeung]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture4.pdf slides]: [https://www.youtube.com/watch?v=bNb2fEVKeEo Lecture 5 | Convolutional Neural Networks] by [[Mathematician#SYeung|Serena Yeung]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture5.pdf slides]<br/>{{#evu:https://www.youtube.com/watch?v=bNb2fEVKeEo|alignment=left|valignment=top}}: [https://www.youtube.com/watch?v=wEoyxE0GP2M Lecture 6 | Training Neural Networks I] by [[Mathematician#SYeung|Serena Yeung]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture6.pdf slides]: [https://www.youtube.com/watch?v=_JB0AO7QxSA Lecture 7 | Training Neural Networks II] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture7.pdf slides]: [https://www.youtube.com/watch?v=6SlgtELqOWc Lecture 8 | Deep Learning Software] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture8.pdf slides]: [https://www.youtube.com/watch?v=DAOcjicFr1Y Lecture 9 | CNN Architectures] by [[Mathematician#SYeung|Serena Yeung]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture9.pdf slides]: [https://www.youtube.com/watch?v=6niqTuYFZLQ Lecture 10 | Recurrent Neural Networks] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture10.pdf slides]: [https://www.youtube.com/watch?v=nDPWywWRIRo Lecture 11 | Detection and Segmentation] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture11.pdf slides]: [https://www.youtube.com/watch?v=6wcs6szJWMY Lecture 12 | Visualizing and Understanding] by [[Mathematician#JustinJohnson|Justin Johnson]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture12.pdf slides]: [https://www.youtube.com/watch?v=5WoItGTWV54 Lecture 13 | Generative Models] by [[Mathematician#SYeung|Serena Yeung]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture13.pdf slides]: [https://www.youtube.com/watch?v=lvoHnicueoE Lecture 14 | Deep Reinforcement Learning] by [[Mathematician#SYeung|Serena Yeung]], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture14.pdf slides]: [https://www.youtube.com/watch?v=eZdOkDtYMoo Lecture 15 | Efficient Methods and Hardware for Deep Learning] by [https://scholar.google.com/citations?user=E0iCaa4AAAAJ&hl=en Song Han], [http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture15.pdf slides]==Music'''==
* [https://en.wikipedia.org/wiki/John_Zorn#The_Dreamers The Dreamers] & [[:Category:John Zorn|John Zorn]] - Gormenghast, [https://en.wikipedia.org/wiki/Pellucidar:_A_Dreamers_Fantabula Pellucidar: A Dreamers Fantabula] (2015), [https://en.wikipedia.org/wiki/YouTube YouTube] Video
: [[:Category:Marc Ribot|Marc Ribot]], [https://en.wikipedia.org/wiki/Kenny_Wollesen Kenny Wollesen], [https://en.wikipedia.org/wiki/Joey_Baron Joey Baron], [https://en.wikipedia.org/wiki/Jamie_Saft Jamie Saft], [https://en.wikipedia.org/wiki/Trevor_Dunn Trevor Dunn], [https://en.wikipedia.org/wiki/Cyro_Baptista Cyro Baptista], John Zorn
[[Category:Marc Ribot]]
[[Category:John Zorn]]
[[Category:Videos]]
