QUANT dira-t-on? - Series: Machine Learning - Part 1

Regularized Regressions

Linear models obtained with minimizing the SSR (Sum of Square Residuals) are great and easy to grasp. However, rarely all conditions are met and/or as the number of…

Gradient Descent

Gradient Descent is an optimization technique used in many Machine Learning algorithms to find the minimum of a function.…

Linear Regression

A dive into the math behind the linear regression algorithm.

KNN - K Nearest Neighbor

Using KNN in both python and R

Defining Success

When evaluating models for a given ML algorithm, we need to define in advance what would be our metric to measure success. How…

Naive-Bayes - Part 1

Making Naive-Bayes work in R

Intro to Kmeans

Kmeans with regime changes

This post is about how to use Kmeans to classify various market regimes or to use Kmeans to classify financial observations.