Tutorials - Prerequisites

Track 1 (18.11.2018)


Building Interactive Dashboards in Python - First steps with Dash - Mikolaj Olszewski

This tutorial will be highly interactive. Participants are advised to bring their own laptops with the following software installed:

  • Python 3 with packages:
    • pandas
    • numpy
    • dash
    • dash-html-components
    • dash-core-components
    • dash-table
    • plotly
  • Text editor of you choice (for example Atom)

If you had those packages installed, please make sure they're up-to-date. Please also make sure that you're able to run Python scripts from the command line.

Recognize drawings in the browser with Tensorflow.js - Karol Majek, Monika Koprowska

Prerequisites for this tutorial:

- Keras, Tensorflow - python, basic knowledge
- Google Chrome or Firefox browser
  - up to date
  - WebGL support: https://get.webgl.org/
  - Have non zero predictions in this demo: https://storage.googleapis.com/tfjs-examples/mobilenet/dist/index.html
- GitHub account
  - We will use GitHub Pages (github.io)
- Google Colab or Jupyter notebook familiarity
  - We will train model in Colab
- Google account is not required
- Git client is not required


Track 2 (18.11.2018)


Structuring machine learning models by using pipelines - Paweł Jankiewicz

This tutorial assumes scikit-learn familarity and writing simple classes in Python.
The materials will be presented using Jupyter Notebook so please prepare an environment with standard Python data science stack:
- scikit-learn
- pandas 


Serverless Approach to Working with Data - Jakub Nowacki

To run this repo you'll need:
  1. Install Node.js https://nodejs.org/

  2. Install Serverless https://serverless.com/framework/docs/getting-started/
  3. Install Python distribution, e.g. Anaconda https://www.anaconda.com/download/
  4. Install your favorite Python ID, e.g. VSCode https://code.visualstudio.com/; support for JavaScript, NodeJS, YAML etc. is a plus.
  5. Install Git https://git-scm.com/
  6. Register on AWS https://aws.amazon.com/ and install AWS CLI; you should not surpass the free tier.
  7. For Windows 10 users it is useful to have Ubuntu for Windows https://tutorials.ubuntu.com/tutorial/tutorial-ubuntu-on-windows#0
  8. For deployment package builder it is good to have Docker installed (https://www.docker.com/get-started) along with Serverless Python Requirements Plugin (https://www.npmjs.com/package/serverless-python-requirements)
Resolving Docker Toolbox Daemon Is Not Running Error (Windows)

The way to fix Docker Toolbox daemon error is to set a number of environment variables, as follows:

SET DOCKER_TLS_VERIFY=1 SET DOCKER_HOST=tcp://192.168.99.100:2376 SET DOCKER_CERT_PATH=%USERPROFILE%\.docker\machine\machines\default SET DOCKER_MACHINE_NAME=default SET COMPOSE_CONVERT_WINDOWS_PATHS=true

%USERPROFILE% should point to your home directory (you can check it using echo %USERPROFILE%); if it is not set correctly, change manually to your home in DOCKER_CERT_PATH given above.

The description is taken from https://www.mydatahack.com/resolving-docker-deamon-is-not-running-error-from-command-prompt/


Track 3 (21.11.2018)

Introduction to Recommendation Systems -  Piotr Bigaj, Jakub Gasiewski, Przemek Kepczynski

Requirments:

  1. Python 3.6+
  2. Anaconda (numpy, pandas, jupyter notebook)
  3. Tensorflow (if there will be enough time to use WALS)

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