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Notes on deep learning

Teory

Lecture notes for the Stanford class on CNNs: CS231n: Convolutional Neural Networks for Visual Recognition

http://machinelearningmastery.com/crash-course-recurrent-neural-networks-deep-learning/ http://machinelearningmastery.com/implement-backpropagation-algorithm-scratch-python/ http://machinelearningmastery.com/create-algorithm-test-harness-scratch-python/

Tools

Web service: Online live supervision of training process http://machinelearningmastery.com/machine-learning-performance-improvement-cheat-sheet/

http://machinelearningmastery.com/improve-deep-learning-performance/ http://machinelearningmastery.com/feature-importance-and-feature-selection-with-xgboost-in-python/ http://machinelearningmastery.com/gentle-introduction-xgboost-applied-machine-learning/

http://machinelearningmastery.com/image-augmentation-deep-learning-keras/

http://machinelearningmastery.com/feature-selection-machine-learning-python/

http://machinelearningmastery.com/prepare-data-machine-learning-python-scikit-learn/

http://machinelearningmastery.com/visualize-machine-learning-data-python-pandas/

http://machinelearningmastery.com/understand-machine-learning-data-descriptive-statistics-python/

http://machinelearningmastery.com/bagging-and-random-forest-ensemble-algorithms-for-machine-learning/

http://machinelearningmastery.com/question-to-understand-any-machine-learning-algorithm/

Keras

http://machinelearningmastery.com/using-learning-rate-schedules-deep-learning-models-python-keras/ http://machinelearningmastery.com/dropout-regularization-deep-learning-models-keras/ http://machinelearningmastery.com/check-point-deep-learning-models-keras/ Superb guide for getting started with keras and CNNs: Building powerful image classification models using very little data

Visualizing filers by maximizing output for individual classes(interesting, but not that useful): Visualizing Deep Neural Networks Classes and Features

Guide to setting up a simple NN: 5 Step Life-Cycle for Neural Network Models in Keras

Tuning NN hyperparameters using sklearns grid search: How to Grid Search Hyperparameters for Deep Learning Models in Python With Keras

Storing weights and models: Save and Load Your Keras Deep Learning Models

Enumerating layers in the VGG16 model

model.add(ZeroPadding2D((1,1),input_shape=(3,224,224))) #0
model.add(Convolution2D(64, 3, 3, activation='relu'))   #1
model.add(ZeroPadding2D((1,1)))                         #2
model.add(Convolution2D(64, 3, 3, activation='relu'))   #3
model.add(MaxPooling2D((2,2), strides=(2,2)))           #4

model.add(ZeroPadding2D((1,1)))                         #5
model.add(Convolution2D(128, 3, 3, activation='relu'))  #6
model.add(ZeroPadding2D((1,1)))                         #7
model.add(Convolution2D(128, 3, 3, activation='relu'))  #8
model.add(MaxPooling2D((2,2), strides=(2,2)))           #9

model.add(ZeroPadding2D((1,1)))                         #10
model.add(Convolution2D(256, 3, 3, activation='relu'))  #11
model.add(ZeroPadding2D((1,1)))                         #12
model.add(Convolution2D(256, 3, 3, activation='relu'))  #13
model.add(ZeroPadding2D((1,1)))                         #14
model.add(Convolution2D(256, 3, 3, activation='relu'))  #15
model.add(MaxPooling2D((2,2), strides=(2,2)))           #16

model.add(ZeroPadding2D((1,1)))                         #17
model.add(Convolution2D(512, 3, 3, activation='relu'))  #18
model.add(ZeroPadding2D((1,1)))                         #19
model.add(Convolution2D(512, 3, 3, activation='relu'))  #20
model.add(ZeroPadding2D((1,1)))                         #21
model.add(Convolution2D(512, 3, 3, activation='relu'))  #22
model.add(MaxPooling2D((2,2), strides=(2,2)))           #23

model.add(ZeroPadding2D((1,1)))                         #24
model.add(Convolution2D(512, 3, 3, activation='relu'))  #25
model.add(ZeroPadding2D((1,1)))                         #26
model.add(Convolution2D(512, 3, 3, activation='relu'))  #27
model.add(ZeroPadding2D((1,1)))                         #28
model.add(Convolution2D(512, 3, 3, activation='relu'))  #29
model.add(MaxPooling2D((2,2), strides=(2,2)))           #30

Lasagne and nolearn

Deep learning – Convolutional neural networks and feature extraction with Python

TODO

Installing cuda 8.0 Ubuntu

https://github.com/saiprashanths/dl-setup

nvidia driver

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-370