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.