Instructions

Install python 2.7, python-pip and python-dev

Installing python2.7 will update to the latest version of Python 2.7, and python-pip will install Pip which allows us to manage Python packages we would like to use. Some of Jupyter’s dependencies may require compilation, in which case you would need the ability to compile Python C-extensions, so we are installing python-dev as well.

sudo apt-get install -f python2.7 python-pip python-dev

To verify that you have python and pip installed:

python --version
pip --version

Installing Ipython

sudo apt-get install -f ipython ipython-notebook

Installing Jupyter Notebook

-H, --set-home Request that the security policy set the HOME environment variable to the home directory specified by the target user's password database entry. Depending on the policy, this may be the default behavior.

sudo -H pip install jupyter

If any error --> Upgrade pip to the latest version

sudo -H pip install --upgrade pip

Try installing Jupyter again

sudo -H pip install jupyter

Running Jupyter Notebook

jupyter notebook

Install packages

sudo apt-get install -f python-numpy python-pandas python-matplotlib

sudo apt-get install -f build-essential python-dev python-setuptools python-numpy python-scipy libatlas-dev libatlas3gf-base libfreetype6-dev libpng-dev g++ python-matplotlib

sudo apt-get install -f python-numpy-dev g++

sudo -H pip install scikit-learn

To upgrade:

sudo -H pip install --upgrade pandas
sudo -H pip install matplotlib --upgrade

Install seaborn

Download latest version of seaborn .tar.gz

tar -xzf seaborn-file.tar.gz
cd seaborn-path/
sudo python setup.py install

Install matplotlib Toolkits

http://matplotlib.org/1.4.3/mpl_toolkits/index.html

https://peak5390.wordpress.com/2012/12/08/matplotlib-basemap-tutorial-installing-matplotlib-and-basemap/

sudo apt-get install -f python-mpltoolkits.basemap

Install xgboost

git clone --recursive https://github.com/dmlc/xgboost
cd xgboost; cp make/config.mk ./config.mk; make -j4
python setup.py develop --user

Install tensorflow with virtualenv

https://www.tensorflow.org/install/install_linux

sudo apt-get install -f python-pip python-dev python-virtualenv
virtualenv --system-site-packages tensorflow # target diectory
source ~/tensorflow/bin/activate # (tensorflow)$
pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp27-none-linux_x86_64.whl # pip version lower than 8.1 Python 2.7  and cpu only

Activate the virtualenv environment each time you use TensorFlow

source ~/tensorflow/bin/activate

You shoul get something like this: (tensorflow)$

To deactivate:

deactivate

Validate your tensorflow installation

Active your container

python
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print(sess.run(hello))

>>> Hello, TensorFlow!

Uninstalling TensorFlow

rm -r targetDirectory

Install pydot and graphviz (for NN graph)

sudo apt-get install -f python-pydot
sudo -H pip install pydot-ng
sudo -H pip install pydot --upgrade

sudo apt-get install -f graphviz

Install plotly (for EDA)

sudo -h pip install plotly

Install keras

https://keras.io/#installation

Required dependencies

• numpy, scipy
• yaml
• HDF5 and h5py (optional, required if you use model saving/loading functions)
• Optional but recommended if you use CNNs: cuDNN.

sudo apt-get install -f python-yaml
sudo apt-get install -f libhdf5-dev
sudo apt-get install -f python-h5py

Install keras

sudo -H pip install keras

Using a virtualenv in an IPython notebook (install kernels)

https://help.pythonanywhere.com/pages/IPythonNotebookVirtualenvs/

source ~/tensorflow/bin/activate
python2 -m ipykernel install --user
python -m ipykernel install --user --name tensorflow --display-name "Python tensorflow"

Using Jupyter Notebook

Automatically, Jupyter Notebook will show all of the files and folders in the directory it is run from.

To create a new notebook file, select New > Python 2 from the top right pull-down menu.

This will open a notebook. We can now run Python code in the cell or change the cell to markdown. For example, change the first cell to accept Markdown by clicking Cell > Cell Type > Markdown from the top navigation bar. We can now write notes using Markdown and even include equations written in LaTeX by putting them between the $$ symbols. For example, type the following into the cell after changing it to markdown:

# Simple Equation

Let us now implement the following equation:
$$ y = x^2$$

where $x = 2$

To turn the markdown into rich text, press CTRL+ENTER:

You can use the markdown cells to make notes and document your code. Let's implement that simple equation and print the result. Select Insert > Insert Cell Below to insert and cell and enter the following code:

x = 2
y = x*x
print y