Your project’s codebase keeps growing and it daunts you. We’ve all been there. Maybe this tool can help you. Felix Plagge has written a package that creates a call graph for any Python script. In this article, he first explains what project graphs are useful for and then explains the installation and usage of his package called project_graph.
Do you want to learn Python? Or maybe you need a little reminder from time to time while coding? That’s exactly why cheatsheets were invented! Our first cheatsheet with Python basics is the start of a new blog series, where more cheatsheets will follow in our unique STATWORX style.
In this blog post, Jannik will show you how to deploy your machine learning models as a REST API and how to make requests to the API from within your Python code.
As data scientists, getting our hands on the data we need is often the most challenging part of a project. In practice, we tend to make life hard on ourselves because we don’t use the best tools for the job. Well no longer! Read on to learn how can you can harness Airflow to orchestrate your own ETL processes like a pro!
Have a look at what my team and I worked on during the Permafrost Hackathon in Zurich. The goal was to detect movements from multitemporal images. Since the images didn’t have any labels, we used unsupervised learning methods. Check it out, yo!
For all those, who are struggling with the (kind of weird) Johns Hopkins University COVID-19 case data CSV files, we’ve created a free API that makes it easy to integrate the latest worldwide COVID-19 data into your application.
This blog is a hands-on experience in Dash, presenting core components, how to display figures with callbacks, supplying you with a working web application to play with, and the resources to build your own. Dash is a powerful tool for Python developers. Developed by the team behind Plotly, Dash is an open-source framework built on top of Flask, Plotly.js, and React.js.