Since these posts aren’t getting much traction, I haven’t made any in what feels like an eternity. Since I last posted, I have made lots of improvements to the game: You can check out all these improvements on the Steam demo and on itch. Additionally, I’ve participated in a couple of festivals, getting to ~250… Continue reading The Ouroboros King, content and aesthetics update
In May 2022 the Naga tribe was introduced to HS Battlegrounds. From the start, the tribe was completely OP with decent early-game units what and crazy late-game scaling. Since then they’ve been nerfed twice, lowering both the initial stats and scaling potential of some minions. In this post I’ll help you build a Naga board… Continue reading HS Battlegrounds, optimizing your late game Naga board (post-nerf)
Simulation is a very potent tool that is often lacking in many data scientists’ toolkits. In this article, I will teach you how to use simulation in combination with other analytical tools. I will be sharing some educational and professional examples of simulation with Python code. If you are a data scientist (or on the… Continue reading How to use simulations in data science
When you start learning, it’s very hard to have a clear direction. You often waste time on uninteresting, useless, or outdated topics. You wander and run in circles. However, once you’ve mastered the topic, it’s easy to look back and see the fastest path from noob to pro. If you only could go back in… Continue reading 13 essential tips for learning machine learning and data science
When I learned data science I didn’t know where to start, so I wasted many hours learning only tangentially useful stuff. Now, after more than five years as a data science consultant, I know what I would’ve done differently. In this article, I will offer you a roadmap on how self-learn data science with links… Continue reading How to self-learn data science from scratch
In this article, I’ll give you a structured approach to getting a data science job. In fact, I’ll be sharing all the techniques that have helped me get offers from startups and management consulting firms, along with examples of my own resume and project portfolio. Additionally, I’ll talk about what I look for when screening… Continue reading How to get a job (in data science)
You’ve just finished training a credit risk tree model with a whooping 57 AUC score, and you feel great. And you should. But let’s dig deeper. How much better will this model be than using no model? Or than using the previous model which had an AUC of 48? Have you ever wondered what the… Continue reading How to estimate the impact of algorithms
You are a student finishing their bachelor’s degree and unsure of what to do next. Or perhaps you are a professional considering a change of industry. You may even be a PhD that wants to transition into the private sector. Whatever your origin, what concerns you now is how to accomplish this change. And you… Continue reading When is a master’s degree the right way into Data Science?