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Introduction to deep-learning: Setup

Installing Python using Anaconda

Python is a popular language for scientific computing, and a frequent choice for machine learning as well. Installing all of its scientific packages individually can be a bit difficult, however, so we recommend the installer Anaconda which includes most (but not all) of the software you will need.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.4 is fine). Also, please set up your python environment at least a day in advance of the workshop. If you encounter problems with the installation procedure, ask your workshop organizers via e-mail for assistance so you are ready to go as soon as the workshop begins.

Windows - Video tutorial

  1. Open with your web browser.

  2. Download the Python 3 installer for Windows.

  3. Double-click the executable and install Python 3 using MOST of the default settings. The only exception is to check the Make Anaconda the default Python option.

Mac OS X - Video tutorial

  1. Open with your web browser.

  2. Download the Python 3 installer for OS X.

  3. Install Python 3 using all of the defaults for installation.


Note that the following installation steps require you to work from the shell. If you run into any difficulties, please request help before the workshop begins.

  1. Open with your web browser.

  2. Download the Python 3 installer for Linux.

  3. Install Python 3 using all of the defaults for installation.

    a. Open a terminal window.

    b. Navigate to the folder where you downloaded the installer

    c. Type

    $ bash Anaconda3-

    and press tab. The name of the file you just downloaded should appear.

    d. Press enter.

    e. Follow the text-only prompts. When the license agreement appears (a colon will be present at the bottom of the screen) hold the down arrow until the bottom of the text. Type yes and press enter to approve the license. Press enter again to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).

Installing the required packages

Conda is the package management system associated with Anaconda and runs on Windows, macOS and Linux. Conda should already be available in your system once you installed Anaconda successfully. Conda thus works regardless of the operating system. Make sure you have an up-to-date version of Conda running. See these instructions for updating Conda if required.

Open a terminal and type the command:

conda install tensorflow seaborn scikit-learn pandas

Note that modern versions of Tensorflow make Keras available as a module.

Troubleshooting for Windows

It is possible that Windows users will run into version conflicts. If you are on Windows and get errors running the command, you can try installing the packages using pip:

pip install tensorflow>=2.5 seaborn scikit-learn pandas

pip is the package management system for Python software packages. It is integrated into your local Python installation and runs regardless of your operating system too.

Starting a Jupyter Notebook

We will teach using Python in a Jupyter notebook, a programming environment that runs in a web browser. Jupyter requires a reasonably up-to-date browser, preferably a current version of Chrome, Safari, or Firefox (note that Internet Explorer version 9 and below are not supported). If you installed Python using Anaconda, Jupyter should already be on your system. If you did not use Anaconda, use the Python package manager pip (see the Jupyter website for details.)

To start the notebook, open a terminal and type the command:

$ jupyter notebook

To start the Python interpreter without the notebook, open a terminal or git bash and type the command:

$ python

Check your setup

To check whether all packages installed correctly, start a jupyter notebook as explained above. Run the following lines of code:

import sklearn
print('sklearn version: ', sklearn.__version__)

import seaborn
print('seaborn version: ', seaborn.__version__)

import pandas
print('pandas version: ', pandas.__version__)

from tensorflow import keras
print('Keras version: ', keras.__version__)

This should output the versions of all required packages without giving errors. Most versions will work fine with this lesson, but for Keras, the minimum version is 2.2.4, and for sklearn the minimum version is 0.22.

Fallback option: cloud environment

If a local installation does not work for you, it is also possible to run this lesson in Google colab. If you open a notebook here, the required packages are already pre-installed.

Downloading the required datasets

Download the weather dataset prediction csv and BBQ labels.