Explore how to calculate the average of a set of circular data.

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# Baeldung Author

## Gabriele De Luca

Gabriele specializes in artificial intelligence and innovation and on the impact of technology on society. He has authored several scientific papers in the sectors of machine learning, natural language processing, network theory, and multi-agent simulations. On Baeldung he contributes to the section on computer science, where he publishes articles on the theory behind machine learning and artificial intelligence.

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

## Baeldung on Computer Science

- All
- Machine Learning (16)
- Math and Logic (14)
- Deep Learning (11)
- Algorithms (9)
- Artificial Intelligence (8)
- Programming (6)
- Latex (5)
- Security (2)
- Graphs (2)
- Core Concepts (2)
- Sorting (1)
- OS (1)
- Networking (1)
- Graph Theory (1)
- Data Structures (1)

### Is a Markov Chain the Same as a Finite State Machine?

Filed under Artificial Intelligence

Explore the differences and the similarities between finite-state machines and Markov chains.

### Differences Between Strong-AI and Weak-AI

Filed under Artificial Intelligence

Explore the differences between strong-AI and weak-AI.

### Basic Concepts of Machine Learning

Filed under Machine Learning

Explore the basic concepts of machine learning.

### What is Selection Bias and How Can We Prevent It?

Filed under Artificial Intelligence, Math and Logic

Explore the methods for preventing selection bias when we conduct statistical analysis.

### Feature Selection and Reduction for Text Classification

Filed under Deep Learning, Machine Learning

Explore the most common techniques for feature selection and reduction for text classification.

### An Algorithm for Inflating and Deflating Polygons

Filed under Algorithms, Math and Logic

Explore how to inflate or deflate a polygon utilizing homothety and offsetting.

### State Machines: Components, Representations, Applications

Filed under Deep Learning, Machine Learning

Explore the components, representations, and applications of finite-state machines.

### Trade-offs Between Accuracy and the Number of Support Vectors in SVMs

Filed under Deep Learning, Machine Learning

Explore the relationship between the number of support vectors and the performances of a support vector classifier.

### The Difference Between a Method and a Function

Filed under Core Concepts, Programming

Learn a conceptual difference between methods and functions.

### Ackermann Function

Filed under Math and Logic

Explore the Ackermann function and the problems associated with its computation.

### Alternatives of Ten – Binary, Octal, Hexadecimal

Filed under Math and Logic, OS

Explore numeral systems and their associated concepts.

### Ugly Duckling Theorem

Filed under Deep Learning, Machine Learning

Learn about the ugly duckling theorem in its relationship with algorithmic bias.

### Normalize Features of a Table

Filed under Artificial Intelligence

Learn how to normalize the features of a table or dataset.

### Haversine Formula

Filed under Math and Logic

Learn about the Haversine formula for calculating great circle distances in spherical surfaces.

### Algorithm for “Nice” Grid Line Intervals on a Graph

Filed under Algorithms, Latex

Explore an algorithm for placing nice gridlines on a bar chart.

### The Difference Between Lower Bound and Tight Bound

Filed under Math and Logic

Explore the difference between Omega notation for lower bounds and the Theta notation for tight bounds.

### Roulette Selection in Genetic Algorithms

Filed under Algorithms

Study the roulette wheel selection method for genetic algorithms.

### Geofencing – Determining Whether a Point is Inside of a Polygon

Filed under Algorithms

Learn how to determine whether a point is inside a polygon or not.

### Choosing an Attractive Linear Scale for a Graph’s Y Axis

Filed under Algorithms, Latex

Learn how to determine a nice scale for the Y axis in a chart.

### Converting a Uniform Distribution to a Normal Distribution

Filed under Artificial Intelligence

Explore how to generate a pseudorandom variable that’s distributed normally.

### Gradient Descent vs. Newton’s Gradient Descent

Filed under Artificial Intelligence

Compare gradient descent and Newton’s method for finding the minima in a cost function.

### How Does the Google “Did You Mean?” Algorithm Work?

Filed under Algorithms, Artificial Intelligence

Learn how the “Did you mean?” algorithm works in Google.

### Worst Sorting Algorithms – What to Avoid

Filed under Sorting

Study sorting algorithms that are even worse than Bogosort.

### Brute Force Algorithm in Cybersecurity and String Search

Filed under Algorithms, Security

Explore the definition of a brute-force search for combinatorial problems and for fixed-length strings.

### What is a DMZ in Networking?

Filed under Networking, Security

Learn about the concept of demilitarized zones for cybersecurity and networking.

### What is Cross-Entropy?

Filed under Machine Learning

Study the definition of cross-entropy.

### Advantages and Disadvantages of Neural Networks Against SVMs

Filed under Deep Learning, Machine Learning

Explore the advantages of ANNs against SVMs, and vice versa.

### Graph Auto-Layout Algorithm

Filed under Programming

Explore the principles behind the layout of graphs in drawings.

### Draw a Chart Using LaTeX

Filed under Latex

Learn how to draw basic charts in LaTeX.

### Draw a Graph Using LaTeX

Filed under Latex

Learn how to draw graphs using LaTeX.

### Generating Dependency Graphs With Text

Filed under Latex, Programming

Learn about the tools that we can use to generate dependency graphs.

### Graphs: Sparse vs Dense

Filed under Data Structures, Graphs

Explore the definition of density in a graph in relation to its size, order, and the maximum number of edges.

### Neural Network Architecture: Criteria for Choosing the Number and Size of Hidden Layers

Filed under Deep Learning, Machine Learning

Explore methods for identifying the correct size and number of hidden layers in a neural network.

### What’s the Difference Between a Word and a Byte?

Filed under Programming

Learn the characteristics of words and bytes and discussed their different relationships with memory and processors.

### Training Data for Sentiment Analysis

Filed under Deep Learning, Machine Learning

Learn the basics of the methodology for sentiment analysis and explore public datasets for supervised sentiment analysis.

### Looping in a Spiral

Filed under Algorithms

Explore how to loop over the elements of a matrix in a square spiral pattern.

### What the Correlation Coefficient Actually Represents

Filed under Algorithms, Math and Logic

Explore the concept of correlation for bivariate distributions.

### Differences Between Classification and Clustering

Filed under Machine Learning

Learn about the difference between classification and clustering.

### Understanding Randomness

Filed under Core Concepts

Explore the ontological and epistemological foundations of randomness.

### What is a Policy in Reinforcement Learning?

Filed under Deep Learning, Machine Learning

Explore the concept of policy for reinforcement learning agents

### What is the Difference Between Gradient Descent and Gradient Ascent?

Filed under Deep Learning, Math and Logic

Learn about gradient descent and gradient ascent and when to use them.

### SVM Vs Neural Network

Filed under Machine Learning

Explore the main similarities and differences between support vector machines and neural networks.

### Support Vector Machines (SVM)

Filed under Machine Learning

Explore the theoretical foundation of support vector machines.

### When Not to Use Regular Expressions?

Filed under Programming

Explore some common cases in which we shouldn’t use RegExes.

### Regular Expressions

Filed under Programming

Study the syntactic rules for regular expressions.

### Boolean Algebra: Basic Laws

Filed under Math and Logic

Study the basic laws of Boolean algebra and learn how to apply them for the simplification of Boolean expressions.

### Introduction to Convolutional Neural Networks

Filed under Deep Learning, Machine Learning

Study the main characteristics of convolutional neural networks.

### Why Does the Cost Function of Logistic Regression Have a Logarithmic Expression?

Filed under Math and Logic

Discover the reasoning according to which we prefer to use logarithmic functions such as log-likelihood as cost functions for logistic regression.

### Linear Regression vs. Logistic Regression

Filed under Machine Learning, Math and Logic

Explore the main similarities and differences between linear and logistic regression.

### First-Order Logic

Filed under Math and Logic

Learn the conceptual bases of first-order logic and explore how to derive it as a generalization from propositional logic.

### Bias in Neural Networks

Filed under Deep Learning, Machine Learning

Learn the formal definition of bias in measurements, predictions, and neural networks.

### Propositional Logic

Filed under Math and Logic

Explore the foundational concepts for propositional logic, which include the idea of proposition and declarative sentences.

### Introduction to Graph Theory

Filed under Graph Theory

Learn the conceptual bases of graph theory.

### How to Build a Knowledge Graph?

Filed under Artificial Intelligence, Graphs

Learn about the theory behind Knowledge Bases, expert systems, and their associated knowledge graphs.