This article analyses 30,000 unique Data Science blog posts from the last year to get to the bottom of what the Data Science community has been discussing. This post looks at the most discussed -- and most popular -- technologies of the year.
Xanthus is a Deep Learning (DL) library built on top of Tensorflow and uses the Keras API to implement various neural recommendation model architectures. This post benchmarks the models implemented in Xanthus against some popular 'classic' matrix factorisation models.
Streamlit is a minimal, modern data visualization framework that's rapidly becoming the go-to dataapp framework in the Python ecosystem. This post introduces Streamlit, and shows you how to securely and scalably deploy your Streamlit apps with Google App Engine.
This post introduces Xanthus - a new open source Deep Learning package built on TensorFlow 2.0 for quickly and easily building state of the art recommendation models in Python.
Creating CLIs can help improve accessibility and reuse of your scripts and packages, but they can also be a bit of a pain to set up and maintain. Fire makes building CLIs for your latest ML pipeline a breeze.
TQDM is a tiny Python package that lets you add customisable progress bars to your code. Ideal for some those nasty multi-hour model training jobs.