Learn how to use the proportion of variance to choose the number of components in PCA.

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# Baeldung Author

## Saulo Barreto

Currently, I'm pursuing my Master's Degree at the University of Debrecen. In my field of research in Machine Learning, I'm interested in Generalization Theory, Hyperparameters Analysis, and the influence of synthetic data in training neural networks for Computer Vision applications. Moreover, I'm always trying to expand my knowledge in AI and Computer Science topics.

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

## Baeldung on Computer Science

- All
- Machine Learning (12)
- Deep Learning (5)
- Math and Logic (3)
- Computer Vision (3)
- Programming (2)
- Data Science (2)
- Methodology (1)

### What Is a Digital Twin?

Filed under Methodology

Learn about digital twins, models that allow simulation for real-world processes, objects, and places in real time.

### What Does Learning Rate Warm-up Mean?

Filed under Machine Learning

Explore different strategies of defining the learning rate in order to warm up the training stage.

### How to Calculate Signal-To-Noise Ratio?

Filed under Math and Logic

Learn the definition of SNR and review examples of how to calculate and interpret the SNR in different scenarios.

### What Are i.i.d. Random Variables?

Filed under Math and Logic

Learn what it means when we say that random variables are independent and identically distributed and why this isn’t always easy to check.

### Open Source Explained

Filed under Programming

Learn about the open-source movement.

### What Is Singular Value Decomposition?

Filed under Machine Learning, Math and Logic

Explore the relevance of and how to compute an SVD of a matrix.

### Statistics: Correlation vs. Regression

Filed under Data Science

Learn the difference between correlation and regression, two statistical techniques we use to analyze the relationship between variables.

### What Is the No Free Lunch Theorem?

Filed under Machine Learning

Learn about the No Free Lunch Theorem.

### Differences Between Computer Vision and Image Processing

Filed under Computer Vision

Explore the differences between computer vision and image processing.

### What Are Image Histograms?

Filed under Computer Vision

Learn what image histograms are and when to use them.

### Instance Segmentation vs. Semantic Segmentation

Filed under Computer Vision, Deep Learning

Explore semantic and instance segmentation.

### Data Augmentation

Filed under Deep Learning, Machine Learning

Explore data augmentation techniques.

### What Is Fine-Tuning in Neural Networks?

Filed under Machine Learning

Learn about fine-tuning neural networks.

### Differences Between Backpropagation and Feedforward Networks

Filed under Deep Learning, Machine Learning

Learn the differences between backpropagation and feedforward neural networks.

### Real-Life Examples of Supervised Learning and Unsupervised Learning

Filed under Deep Learning, Machine Learning

Explore some real-life examples of supervised and unsupervised learning.

### Markov Decision Process: How Does Value Iteration Work?

Filed under Machine Learning

Learn how to implement a dynamic programming algorithm to find the optimal policy of an RL problem, namely the value iteration strategy.

### Choosing a Learning Rate

Filed under Machine Learning

Explore different strategies to update the weights during the training phase of any machine learning model.

### How Do “20 Questions” AI Algorithms Work?

Filed under Machine Learning

Learn how we can implement the 20 Questions Game using a nonparametric model called a decision tree.

### High-Level Languages vs. Low-Level Languages

Filed under Programming

Explore the differences between high-level and low-level languages.

### Why Mini-Batch Size Is Better Than One Single “Batch” With All Training Data

Filed under Deep Learning, Machine Learning

Learn the main differences between using the whole dataset as a batch to update the model and using a mini-batch