Not a whole lot for Trump to undo

ColabFold has changed the game for amateur protein folding analysis

Getting started with Deepmind's revolutionary model for protein folding

A continuation of genome sequencing analysis

A good step but not nearly enough

Introductory methods for genome sequencing

Like many music enthusiasts, the most used app on my phone by far is Spotify. One of my favorite features is their daily or weekly curated playlists based on your listening tastes. Spotify users can get as many as six curated ‘Daily Mixes’ of 50 songs, as well as a ‘Discover Weekly’ of 30 songs updated every Monday. That’s more than 2k songs a Spotify user will be recommended in a given week. Assuming an everage of 3 minutes per song, even a dedicated user would find themselves spending more than 15 hours a day to listen to all of that content. That…wouldn’t be healthy. But Spotify’s recommendations are good! And I always feel like I’m losing something when these curated playlists expire before I can enjoy all or even most of the songs they contain. Or at least I did, until I found a way around it. In this articule, I’m going to take you through Spotify’s API and how you can solve this problem with some beginner to intermediate Python skills. Introduction to Spotify’s API Spotify has made several public APIs for developers to interact with their application. Some of the marketed use cases are exploring Spotify’s music catalogue, queuing songs, and creating playlists. You can credential yourself using this documentation guide . I’d walk you through it myself but I don’t work for Spotify and I want to get to the interesting stuff. In the remainder of this article I will be talking leveraging Spotipy , an open source library for python developers to access Spotify’s Web API. NOTE : At the time of writing, Spotipy’s active version was 2.22.1, later versions may not have all of the same functionality available.

Evolutionary strategies for feature engineering

Another recap of analytical methods

Another experiment with NASA data

creating synthetic data for incomplete NASA dataset

An exploration of different symptoms experienced after the acute illness

Speech given at the University of Virginia on July 31st, 2022

Part 3 - a recap of methodology

Online gaming communities need to work harder to close the gap for their female users.

Hospitals hold the key to predicting how long a product will be on the shelf.

Part 2 - Extending methods with variational autoencoders

The game you're playing has probably never been played before.

Part 1 - Exploring and classifying more covid genome data