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.

Decision Trees are versatile Machine Learning algorithms that can perform both classification and regression tasks. In this post, we will learn how they use different cost functions to measure their performance depending on the type of problem they are solving.

Regression is a statistical technique that helps you to estimate the relationship between a dependent variable and one or more independent variables. It is basically the simplest machine learning algorithm you can imagine. For example, you can use regression to find out how the price of a house depends on its size, location, number of rooms, etc.

Backpropagation is a popular algorithm used in training neural networks, which allows the network to learn from the input data and improve its performance over time. It is essentially a way to update the weights and biases of the network by propagating errors backwards from the output layer to the input layer.

Have you ever had to analyze data with a complex structure, such as nested or hierarchical data, and found yourself struggling to find a suitable statistical model? If so, you might want to consider using linear mixed effects models.