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.
How do we interact with machine learning models in practice? In the second part of our 4-part blog series on car model classification, you will learn how models can be deployed using TensorFlow Serving, and how we can run model queries.
In this 4-part blog series on car model classification, we want to illustrate how an end-to-end deep learning project can be implemented. In the first part, we will show how you can use transfer learning to tackle car image classification. In particular, you will learn how a pre-trained ResNet model can be fine-tuned to tackle a downstream task.
The objective of this article is to show that fine-tuning Tesseract OCR on a small sample of data can already dramatically improve its OCR performance.
In this blog post, our colleague Lukas gives you a high-level introduction to RDS files (vs. RData files) and serialization. The function checks whether there is already an RDS with the same name in the path, renames it if required, and provides it with a timestamp and a reference ARCHIVED_ON_xx. The function then saves the new RDS under the specified name.
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!
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.
In this blog post, Matthias shows you how to write and structure code even faster and more efficiently. Learn how to define keyboard shortcuts in RStudio with his step-by-step tutorial.
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