Getting started

To be able to follow the workshop exercises, you are going to need a laptop with Anaconda and several Python packages installed. Following instruction are geared for Mac or Ubuntu linux users.

Download and install Anaconda

Please go to the following website: https://www.continuum.io/downloads download and install the latest Anaconda version for Python 2.7 (or Python 3) for your operating system.

Note: we are going to need Anaconda 4.1.x or later (the current latest is 5.0.0)

After that, type:

conda --help

and read the manual.

Check-out the git repository with the exercise

Once Anaconda is ready, checkout the course repository and and proceed with setting up the environment:

git clone https://github.com/ASvyatkovskiy/PythonWorkshop

If you do not have git and do not wish to install it, just download the repository as zip, and unpack it:

wget https://github.com/ASvyatkovskiy/PythonWorkshop/archive/master.zip
#For Mac users:
#curl -O https://github.com/ASvyatkovskiy/PythonWorkshop/archive/master.zip
unzip master.zip

Create isolated Anaconda environment

Change into the course folder, then type:

#cd PythonWorkshop
conda create --name PythonWorkshop --file requirements.txt
source activate PythonWorkshop

Installing Tensorflow

All of the third-part Python packages should be installed by conda. Some packages might cause installation errors depending on your OS. If this happens, select a binary and install protobufs, and TensorFlow. For this workshop, we will use CPU-only version of Tensorflow (feel free to use GPU version, if your laptop has a GPU).

Mac users:

#source activate PythonWorkshop
pip install --user --upgrade protobuf
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.0.0-py2-none-any.whl
pip install --user --upgrade $TF_BINARY_URL
pip install --user --upgrade Pillow

Ubuntu linux users:

sudo apt-get install --user python-pip python-dev python-matplotlib
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.0-cp27-none-linux_x86_64.whl
sudo pip install --user --upgrade $TF_BINARY_URL
sudo pip install --user --upgrade Pillow

Test the installation was succesfull, launch the Jupyter notebook

jupyter notebook

create a new notebook selecting the Python kernel using your anaconda environment from the upper right dropdown menu, and type:

In [1]: import tensorflow as tf
        tf.__version__
        
Out[1]: 1.0.0

Start the interactive notebook

Change to the the repository folder, switch to the Spring2017 local branch, and start interactive jupyter (ipython) notebook:

cd PythonWorkshop
jupyter notebook

After the notebook is opened, navigate to the workshop folder and open the 1.PythonBasics.ipynb from the browser window.

ASvyatkovskiy / PythonWorkshop