mlds-tools

A Collection of helpful resources for ML & DS projects.

The prime purpose of this repository is to house code that is often re-used in common TechLabs Berlin workshops. Most of these pertain to the Data Science track and should be of most interest to those learners.

Additionally, some of the tools and templates introduced in the workshops have been made in to re-usable components such as:

• A docker image to host a self-contained SQL Runner sandbox environment
• Application and helper code (with examples) to run simple flask server, streamlit apps
• Notebook to demonstrate advanced data manipulation and handling, including generation of synthetic data datasets!

Preparing for the Workshop

This preparation guide is a supporting document for the talk "An Intro to Containerization: Hands-on Tutorial with Docker" as part of the TechLabs Berlin Summer 23 Workshop Weekend.

Kindly complete these steps prior to attending the workshop! ❤️️

The content of the tutorial can be accessed here.

Docker

As the title suggests, Docker is our tool of choice for this workshop. It is an open platform that enables development, shipping and productionization of application code in a containerized manner. More about Docker will be covered in our workshop.

Requirement: To prepare for the workshop, we request that you download and install the Docker Desktop application. Please follow through all of the download and installation instructions for your operating system. Get Docker!

Note regarding installation

For advanced users, feel free to use your tool of choice to install Docker, if you do not already have it on your machine. We currently recommend the interactive installer as the simplest way to get Docker installed on Apple silicon.

PSQL

In our demo we will be target deploying a simple app with a database. For this purpose we will need to select a database and install the required binaries to work with that database on your local machine.

For this tutorial we will be working with PostGresSQL

Please make sure you download and install psql for your operating system. (For mac users we would recommend the "installing with HomeBrew" option.)

Heroku (Optional)

Heroku is a platform as a service (PaaS) that enables developers to build, run, and operate applications entirely in the cloud. It is one of the platforms of choice to deploy small, simple apps on a quick tier. We will be using it as part of this workshop to deploy our application to the cloud and make it available to anyone over the internet.

This section is optional since it is mostly to demo deployment and not really a part of the tutorial.

Installing the Heroku CLI

Documentation for correct installation of this tool can be found on the official Heroku Dev Center. Please follow all the instructions here to get the tool setup for your operating system.

Get Started with the Heroku CLI

After you install the CLI, run the heroku login command.

heroku login

This will alow you to authenticate your account via a browser window so that the CLI can store your credentials. You are now setup to work with the Heroku CLI.

Navigating the Workshop

That's all for now!

The tutorial will be conducted in our workshop on Saturday, August 26th at 11 AM CEST. All further instructions to navigate the tutorial will be provided on that day

We look forward to hosting you all 🌈

Appendix

Past Workshop Weekends

Quick Back-ends for Data Project MVPs (ST22)

To participate and navigate through all notebooks that were part of the this TechLabs Berlin Workshop, navigate and follow the instructions here.

Fake it, till you make it: Prototyping for Data Projects (ST21)

• Contains streamlit code used in workshop demonstration
• Simple "Hero" dashboard example