Fast AI Tutorial

Reference

• https://github.com/fastai/courses.git
• http://course.fast.ai/

Lesson 1: Image Recognition

Get data

• https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition/data

Kaggle CLI

• Create profile at https://www.kaggle.com/
• On terminal: pip install kaggle-cli
• kg config -g -u [username] -p [password] -c dogs-vs-cats-redux-kernels-edition
• Go to https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition and accept competition requirements (by downloading the data)
• On terminal: kg download

Arrange data

$ sh arrange_data.sh

Reference

• BPTT algorithm
  • https://en.wikipedia.org/wiki/Backpropagation_through_time
• ImageNet
  • http://image-net.org/explore.php

Memo to train model by using GPU

• modify ~/.theanorc

[global]
floatX = float32
device = gpu
optimizer = fast_run

[lib]
cnmem = 0.8

[nvcc]
fastmath = True

[blas]
ldflags = -llapack -lblas

• modify ~/.keras/keras.json

{
    "image_dim_ordering": "tf", 
    "epsilon": 1e-07, 
    "floatx": "float32", 
    "backend": "tensorflow"
}

• change "tf" to "th"
• change "tensorflow" to "theano"
• "tf" = tensorflow
• "th" = theano

$ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-8.0/lib64
$ export CUDA_HOME=/usr/local/cuda-8.0
$ export PATH=$PATH:/usr/local/cuda-8.0/bin