In this post we will explore a brief example of asynchronous programming in Rust with the Tokio runtime, demonstrating different execution scenarios. This post is aimed at beginners to asynchronous programming.
In this post we will set up a very simple data ingestion process with Rust and AWS Lambda.
The complete code for this example is available on GitHub here.
In this post I will briefly introduce the EM algorithm with two simple examples. The EM algorithm uses an iterative approach to find the Maximum Likelihood estimate for a model with latent variables.
Note I will not provide a thorough coverage of the mathematics but rather focus on two examples of Gaussian Mixture Models.
In this post I list some resources which have helped me to learn Spanish, I hope that they will help you too!
All of the listed resources are (mostly) free, except News In Slow Spanish (and the Latino version), and clearly the textbooks, TV series and films.
Mendelian Randomization is an approach to test for a causal effect from observational data in the presence of certain confounding factors. It uses the measured variation of genes (of known function) to bound the causal effect of a modifiable exposure (environment) on a phenotype (disease). The fundamental idea is that the genotypes are randomly assigned (due to recombination in meiosis under certain assumptions), and this allows them to be used as an instrumental variable.
I've started this blog to save resources which have helped me in learning languages, concepts in statistics, and anything else which I think might help others too.