In machine learning, many matrices are sparse. It is essential to know how to handle this kind of matrix. Sparse vs Dense Matrix First, it is good to know that sparse matrix looks similar to a normal matrix, with rows, columns or other indexes. But a sparse matrix is comprised of mostly zero (0s) values. They are distinct from dense matrices with mostly non-zero values. A matrix is sparse if many...

## Machine learning quick note

Machine learning is a terminology to describe the uses statistical techniques to give computer systems the ability to “learn” (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed. You can think of machine learning as the brains behind AI technologies, and AI technologies do the actions. More technically, machine learning...

## Metrics for regression and classification – quick note

In this article, we review some common metrics and their uses for two main ML problems, i.e. regression and classification. Regression Metrics Most of the blogs have focussed on classification metrics like precision, recall, AUC etc. For a change, I wanted to explore all kinds of metrics including those used in regression as well. MAE and RMSE are the two most popular metrics for continuous...

## Common Loss functions and their uses – quick note

Machines learn by means of a loss function which reflects how well a specific model performs with the given data. If predictions deviate too much from actual results, loss function would yield a very large value. Gradually, with \(optimization\) function, parameters are modified accordingly to reduce the error in prediction. In this article, we will quickly review some common loss functions and...

## Math for ML – Vector norms quick note

Vector norms are used in many machine learning and computer science problems. This article covers some common norms and related applications. From a high school entrance exam… Remember the day (?/?/1998) when I took an exam to a high school, there was a problem of finding the shortest path from A to B knowing that the person can only go left/right or up/down given the following grid of m x...