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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 https://www.anaconda.com/products/distribution 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 https://www.anaconda.com/products/distribution with your web browser.

  2. Download the Python 3 installer for OS X.

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

Linux

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 https://www.anaconda.com/products/distribution 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.

To create a conda environment called dl_workshop with the required packages, open a terminal and type the command:

conda create --name dl_workshop python jupyter seaborn scikit-learn pandas

Activate the newly created environment:

conda activate dl_workshop

Install tensorflow using pip (python’s package manager):

pip install tensorflow

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 within a conda environment:

conda create -n dl_workshop python jupyter
conda activate dl_workshop
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.

Troubleshooting for Macs with Apple silicon chip

Newer Macs (from 2020 onwards) often have a different kind of chip, manufactured by Apple instead of Intel. This can lead to problems installing Tensorflow . If you get errors running the installation command or conda hangs endlessly, you can try installing Tensorflow for Mac with pip:

pip install tensorflow-macos

Starting Jupyter Lab

We will teach using Python in Jupyter lab, 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 jupyter lab, open a terminal and type the command:

$ jupyter lab

To start the Python interpreter without jupyter lab, 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 in jupyter lab 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__)

import tensorflow
print('Tensorflow version: ', tensorflow.__version__)

This should output the versions of all required packages without giving errors. Most versions will work fine with this lesson, but:

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 jupyter notebook here, the required packages are already pre-installed. Note that google colab uses jupyter notebook instead of jupyter lab.

Downloading the required datasets

Download the weather dataset prediction csv and BBQ labels.