Learn more about K-D Trees.

# Baeldung Author

## Hristo Hristov

I am a professional Machine Learning Engineer with 5+ years of experience who loves Computer Science and Mathematics. Sharing my knowledge through articles is my way of giving back to others.

## Here's what I've written (so far):

## Baeldung on Computer Science

- All
- Math and Logic (4)
- Machine Learning (3)
- Trees (2)
- Artificial Intelligence (2)
- Algorithms (2)
- OS (1)
- Deep Learning (1)
- Data Structures (1)
- Computer Vision (1)

### Graph Attention Networks

Filed under Machine Learning

Explore graph neural networks that use attention.

### Quadtrees and Octrees

Filed under Algorithms, Trees

Learn more about Quadtrees and Octrees

### Introduction to Optical Flow

Filed under Computer Vision

Learn about optical flow and its applications with a simplified example.

### The Direct Linear Transform

Filed under Math and Logic

Learn how Direct Linear Transform works between different coordinate systems.

### Attention Mechanism in the Transformers Model

Filed under Artificial Intelligence

Learn about the self-attention mechanism in the transformers architecture.

### The Mahalanobis Distance

Filed under Math and Logic

Learn how to calculate the Mahalanobis Distance

### Off-policy vs. On-policy Reinforcement Learning

Filed under Deep Learning, Machine Learning

Understand two different approaches for training a reinforcement learning agent: on-policy learning and off-policy learning.

### The Call Stack

Filed under OS

Lear how stack memory works.

### An Introduction to the Hidden Markov Model

Filed under Artificial Intelligence, Math and Logic

In this tutorial, we’ll look into the Hidden Markov Model, a type of statistical model.

### An Introduction to the Voronoi Diagram

Filed under Algorithms

A guide to Voronoi diagrams, named after the famous Russian mathematician Georgy Voronoi.

### Intuitive Explanation of the Expectation-Maximization (EM) Technique

Filed under Machine Learning, Math and Logic

Explore the Expectation-Maximization (EM) technique – a popular approach for estimating parameters of probabilistic models