Are you ready for a thrilling data adventure? Noah’s Rug is an awesome data game that challenges you to solve puzzles using a fictional dataset. Every day of Hanukkah, you can light up a candle and discover a piece of a mysterious tapestry. After the last day, you can test your skills in a speedrun mode. You can use any tools you want to explore the data and find the answers. This is a collection of my solutions with some explanations.

You may have seen a preprint online about a weird way of doing text classification tasks. Some researchers used gzip, a compression algorithm, instead of a neural network, and got amazing results (beating BERT and other neural networks for text classification).

Bayesian statistics is a powerful and elegant framework for data analysis that allows us to incorporate prior knowledge, uncertainty, and learning from data into our statistical reasoning. In this entry, I will introduce the conceptual foundations of Bayesian data analysis and show how it can help us solve challenging problems that classical statistics may struggle with.

AutoML is the process of automating the tasks of applying machine learning to real-world problems. I often use this approach as it requires very little investment in tuning models and the results are usually quite competitive. The following is a notebook for a recent kaggle competition.

I’ve been playing around with smart contracts recently. In this post I explain a re-entrancy attacks, a common security flaw in many smart contracts. Re-entrancy attacks occur when a smart contract function temporarily abandons the transaction’s control flow by making an external call to a contract written by unknown or hostile actors. This allows the latter contract to make a recursive call to the primary smart contract function to drain its funds.

From time to time I practice my python skills in codewars. What I like about it is the clever solutions some people come up with. Let’s look at some examples where I learned some useful tricks.