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courses:2017:cs551 [2017/01/20 16:48]
arijit [Slides] |
courses:2017:cs551 [2017/04/12 12:52] (current)
arijit [Slides] |
| * {{ :courses:2017:01_intro_to_dl.pdf |Introduction to Deep Learning}} | * {{ :courses:2017:01_intro_to_dl.pdf |Introduction to Deep Learning}} |
| * {{ :courses:2017:02_linear_algebra.pdf |Overview of linear algebra and probability}} | * {{ :courses:2017:02_linear_algebra.pdf |Overview of linear algebra and probability}} |
| * {{ :courses:2017:03_feature_engg.pdf |Overview of feature engineering}} (Partial set of slides) | * {{ :courses:2017:03_feature_engg.pdf |Overview of feature engineering}} |
| | * {{ :courses:2017:04_neural_network.pdf |Neural Network}} |
| | * {{ :courses:2017:keras.pdf | Demonstration of Keras}} - [[:courses:2017:Installation guide|Installation guide]], [[:courses:2017:Sample code|Sample code]] (Presented by Niraj Kumar) |
| | * {{ :courses:2017:05_dl_network.pdf |Deep Feedforward Network}} |
| | * {{ :courses:2017:06_regularization.pdf |Regularization}} |
| | * {{ :courses:2017:07_optimization.pdf | Optimization of Neural Network}} |
| | * {{ :courses:2017:08_cnn.pdf | Convolutional Neural Network}} |
| | * {{ :courses:2017:09_rnn.pdf | Recurrent Neural Network}} |
| | * {{ :courses:2017:10_practical_methods.pdf | Practical methodology}} |
| | * {{ :courses:2017:11_drl.pdf | Deep Reinforcement Learning}} |
| =====Additional Reading Materials===== | =====Additional Reading Materials===== |
| * {{ :courses:2017:matrixcalculus.pdf|Matrix differentiation}} by Randal J. Barnes, Department of Civil Engineering, University of Minnesota, Minneapolis, Minnesota, USA | * {{ :courses:2017:matrixcalculus.pdf|Matrix differentiation}} by Randal J. Barnes, Department of Civil Engineering, University of Minnesota, Minneapolis, Minnesota, USA |
| * [[http://www.nature.com/nature/journal/v521/n7553/full/nature14539.html|Deep Learning, Nature]] | * [[http://www.nature.com/nature/journal/v521/n7553/full/nature14539.html|Deep Learning, Nature]] |
| | * [[http://ieeexplore.ieee.org/abstract/document/485891/ | Artificial Neural Networks: A tutorial]] |
| | * [[http://www.asimovinstitute.org/neural-network-zoo/|The neural network zoo]] |
| | * [[https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/ | A Step by Step Backpropagation Example]] |
| | * [[http://www.jefkine.com/general/2016/09/05/backpropagation-in-convolutional-neural-networks/|Backpropagation in convolutional neural network]] |
| | * [[http://karpathy.github.io/2015/05/21/rnn-effectiveness/ | Andrej Karpathy blog]] |
| | * [[https://iamtrask.github.io/2015/11/15/anyone-can-code-lstm/ | Blog on LSTM-RNN]] |
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| | =====Information related to projects===== |
| | * {{ :courses:2017:projectlist.pdf |Data resources}} |
| | * [[ :courses:2017:generalinformation| General information]] |
| | * {{ :courses:2017:cs551_project_ideas_v01.pdf |List of projects}} - These are the projects received so far. |
| | * [[ :courses:2017:Final_Project_Report | Final project report]] |