Some information and resources

• IPython (interactive) and Jupyter(notebok for noting and sharing)
  • Good thing about Jupyter: integrate code and document(markdown/html/latex).

  Ex. $softmax(x_i) = \frac{\exp^{x_i}}{\sum_{k=1}^K \exp^{x_k}}$ - Jupyter shortcut keys: https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/

• Tensorflow and Virtual environment: https://www.tensorflow.org/install/install_mac

• Using Jupyter under virtualenv: http://help.pythonanywhere.com/pages/IPythonNotebookVirtualenvs

  • Activate your virtual environment (on Mac)

    source <virtual_env_path>/bin/activate
    

    Note that you should see (your_virtualenv_name) before the prompt when the virtual environment is successfully activated. Here we use (virtualenv) as an example.

  • Install ipython kernel to the virtualenv

    (virtualenv) pip install ipykernel  # pip3 install ipykernel for python3
    

  • Create your kernel

    (virtualenv) python -m ipykernel install --user --name=<your_kernel_name>
    

  • Lauch Jupyter and then you can see the newly added kernel

    (virtualenv) jupyter notebook
    

• Tensorflow tutorial
  • Official tutorial: https://www.tensorflow.org/get_started/
  • Vedios about tensorflow (Chinese): https://morvanzhou.github.io/tutorials/machine-learning/tensorflow/
• Tensorflow validation (hello world)

import tensorflow as tf
hello = tf.constant('Hello, Tensorflow')
sess = tf.Session()
print(sess.run(hello))

Hello, Tensorflow

• slim: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim
• pre-trained model https://github.com/tensorflow/models/tree/master/slim#Pretrained
• GAN https://www.youtube.com/watch?v=0CKeqXl5IY0