Learn about the Student’s t-distribution and how it helps us deal with uncertainty and variability in cases where data is frequently limited or sparse.
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Baeldung Author
Georgios Nanos
I have achieved a Master's degree in Electrical & Computer Engineering from the National Technical University of Athens. Additionally, I obtained a postgraduate degree in Data Science and Machine Learning. I possess extensive experience working with various computer systems, including FPGAs, CPUs, and GPUs. In my leisure time, I enjoy mastering new programming languages and refining strategic thinking through chess.
Here's what I've written (so far):
Baeldung on Computer Science
- All
- Security (6)
- Networking (6)
- Machine Learning (6)
- Software Architecture (5)
- Computer Vision (5)
- Deep Learning (4)
- Programming (3)
- OS (2)
- Data Structures (2)
- Artificial Intelligence (2)
- Graphs (1)
- Data Science (1)
- Concurrency (1)
- Algorithms (1)
Online Transaction Processing vs. Online Analytical Processing
Filed under Software Architecture
Explore OLTP and OLAP.
Understanding the Monte Carlo Simulation
Filed under Algorithms
Explore the Monte Carlo Simulation algorithm.
Blockchains: What Is Proof of Work?
Filed under Networking, Software Architecture
Learn about Proof of Work in the blockchain technology.
Differences Between SQL and NoSQL
Filed under Programming
Explore the differences between SQL and NoSQL databases.
Flash Memory: NOR vs. NAND
Filed under OS
Explore NOR and NAND flash memory.
What and Where Are the Memory Stack and Heap?
Filed under Data Structures, OS, Programming
Explore stack and heap memory in OS.
Distributed Systems: Thin and Thick Clients
Filed under Networking, Software Architecture
Explore the differences between thin and thick clients in distributed systems.
What Is Human-Machine Integration?
Filed under Artificial Intelligence
Explore HMI – a process of combining human expertise with machines to improve individual and industrial automation.
How MAC Flooding and Cloning Attacks Work?
Filed under Networking, Security
Explore how a switched LAN network works and how a MAC Flooding and a MAC Spoofing attack work.
How Do Siamese Networks Work in Image Recognition?
Filed under Computer Vision, Deep Learning
Learn about the Siamese Networks, a class of deep learning architectures that are employed by designing two identical sub-networks.
Neural Networks: Pooling Layers
Filed under Machine Learning
Learn about pooling, a machine-learning technique widely used to reduce input size.
What Is Wardriving?
Filed under Networking
Learn about the term wardriving.
Deep Neural Networks: Padding
Filed under Deep Learning
Learn about padding, a machine learning technique used in image processing to improve model performance and simplify data processing.
Multithreading vs. Hyperthreading
Filed under Concurrency
Explore the most important aspects of multithreading and hyperthreading.
Difference Between Reinforcement Learning and Optimal Control
Filed under Machine Learning
Explore the differences between reinforcement learning and optimal control.
What Are Bridges in a Graph?
Filed under Graphs
Learn about bridges in graphs.
Differences Between a Parametric and Non-parametric Model
Filed under Machine Learning
Learn about parametric and non-parametric models in machine learning.
What Is Maxout in a Neural Network?
Filed under Deep Learning
Explore the maxout activation function, discuss an example, and analyze its main advantages and disadvantages.
Different Network Topologies Explained
Filed under Networking
Explore various network topologies.
Differences Between Luong Attention and Bahdanau Attention
Filed under Machine Learning
Explore the Luong and Bahdanau attention methods.
How Does a Blockchain Work?
Filed under Security
Explore blockchain technology and see how it works.
Computer Vision: Differences Between Low-Level and High-Level Features
Filed under Computer Vision
Walk through low and high-level features in computer vision.
Machine Learning: Flexible and Inflexible Models
Filed under Machine Learning
Learn about model flexibility in machine learning.
Social Engineering
Filed under Security
Learn about Social Engineering, an effective method used by cybercriminals to access the sensitive information of others.
VAE Vs. GAN For Image Generation
Filed under Computer Vision
Learn about VAE and GAN.
What Is Steganography?
Filed under Security
Learn about steganography.
Distributed Systems: Consensus
Filed under Networking, Software Architecture
Explore the concept of Consensus in distributed systems.
What Are Restricted Boltzmann Machines?
Filed under Machine Learning
Explore Restricted Boltzman Machines.
Differences Between a Data Type and a Data Structure
Filed under Data Structures, Programming
Explore data types and data structures, along with their fundamental differences.
What Is Privilege Escalation?
Filed under Security
Explore privilege escalation attacks.
What Are Data Warehouses?
Filed under Software Architecture
Learn about Data Warehouses.
Neural Network and Deep Belief Network
Filed under Artificial Intelligence
Explore Deep Belief Networks.
Generative Adversarial Networks: Discriminator’s Loss and Generator’s Loss
Filed under Deep Learning
Explore GAN’s two main neural networks, the generator and the discriminator, and understand how they play a competitive min-max game trying to replicate a probability distribution.
Fast R-CNN: What is the Purpose of the ROI Layers?
Filed under Computer Vision
Explore the RoI pooling layers and their impact on the speed and accuracy of Fast R-CNN.
What Is a Backdoor?
Filed under Security
Explore the concept of a backdoor.
Object Detection: SSD Vs. YOLO
Filed under Computer Vision
Compare two main object detection algorithms, SSD and YOLO.