The application of historical data for predicting future outcomes is pivotal across various domains, encompassing revenue projections, weather forecasts, stock market trends, sports predictions, and beyond. This dependence on predictive analytics relies on extracting valuable insights from historical data, addressing … Read more
TV series about startup failures, portraying their greedy founders, and the damages of the current startup ecosystem | 1984.design ` ` ` ` ` `
GitHub – kevinlawler/kerf1: Kerf {{ message }} This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. You can’t perform that action at this time. You signed in with … Read more
Previously At the end of Part One, I found myself staring at this BMW F20 GWS (Gangwahlschalter – gear selector switch – thanks to everyone who helped dig up the German name) that I wanted to adapt into an Electric … Read more
I’m overdue to write up some of my vague electric vehicle conversion project, so here’s a small part of it. Note: This post is a journey through the awkward process of reverse engineering. If you’re here to find out what … Read more
Over the past few months, I’ve had the opportunity to mentor aspiring data scientists and enthusiasts of the field. As a data scientist myself, I couldn’t help but notice that all the mentees started off their journey by learning SQL! … Read more
In my previous post, we explored why Honeycomb is implemented as a distributed column store. Just as interesting to consider, though, is why Honeycomb is not implemented in other ways. So in this post, we’re going to dive into the … Read more
Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis. Time series analysis is an essential component of Data Science and Engineering work at industry, from understanding the key statistics … Read more