3mins read Multivariate Gaussian distribution is a fundamental concept in statistics and machine learning that finds applications in various fields, including data […]
11mins read Conventional encoder-decoder architectures for machine translation encoded every source sentence into a fixed-length vector, irrespective of its length, from which […]
4mins read Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP), are both methods for estimating variable from probability distributions or graphical […]
5mins read Introduction When developing Python code we are constantly adding and committing changes. However, nothing stops us from committing low-quality code, e.g. code […]
16mins read Introduction Naïve Bayes algorithm is a supervised classification algorithm based on the Bayes theorem with strong (Naïve) independence among features. In machine learning and data […]
29mins read Sequence-to-sequence models are deep learning models that have achieved a lot of success in tasks like machine translation, text summarization, […]
22mins read An introduction to additive modeling Before we get into boosting, let’s look at an example of what mathematicians call additive modeling because […]
6mins read Most Docker images are run as containers by invoking something along the lines of docker run <image>:<tag>. However, it’s also possible–and […]