A quick and practical guide to text detection in images.
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Baeldung Author
Enes Zvornicanin
Enes is a data scientist with over three years of experience, currently working as a freelancer for Toptal. Enes has a strong background in mathematics, computer science, and machine learning and is passionate about learning and exploring any area related to machine learning.
Here's what I've written (so far):
Baeldung on Computer Science
- All
- Machine Learning (19)
- Deep Learning (9)
- Artificial Intelligence (5)
- Math and Logic (4)
- Computer Vision (4)
- Algorithms (3)
- Data Science (2)
- Searching (1)
Comparison Between BERT and GPT-3 Architectures
Filed under Deep Learning
A quick and practical comparison of BERT and GPT-3 architectures.
Why Does ChatGPT Not Give the Answer All at Once?
Filed under Artificial Intelligence
A quick and practical explanation of why ChatGPT doesn’t give the answer all at once.
What Are the Advantages of Kernel PCA Over Standard PCA?
Filed under Machine Learning
A quick and practical guide to advantages of Kernel PCA.
Data Quality Explained
Filed under Data Science, Machine Learning
Learn the concept of ‘data’, its significance for businesses, and explore methods for assessing data quality.
Why Is ChatGPT Bad at Math?
Filed under Artificial Intelligence
A quick and practical explanation why ChatGPT is bad at math.
How Does ChatGPT Work?
Filed under Artificial Intelligence
A comprehensive introduction to ChatGPT internals.
What Is and Why Use Temperature in Softmax?
Filed under Deep Learning, Machine Learning
A quick and practical guide to using temperature in Softmax.
How Does a Neural Network Recognize Images?
Filed under Computer Vision
A quick and practical guide to how neural networks recognise images?
Automated Machine Learning Explained
Filed under Machine Learning
Understand how automated machine learning works.
Co-occurrence Matrices and Their Uses in NLP
Filed under Machine Learning
Learn more about Co-occurrence Matrices in NLP.
What Is Independent Component Analysis (ICA)?
Filed under Machine Learning
A quick and practical guide to independent component analysis (ICA)
What Are Embedding Layers in Neural Networks?
Filed under Deep Learning
A quick and practical guide to embedding layers in neural networks and their applications.
Introduction to Gibbs Sampling
Filed under Data Science, Machine Learning, Math and Logic
A quick and practical introduction to Gibbs sampling.
Differences Between Transfer Learning and Meta-Learning
Filed under Machine Learning
Learn about the concepts of transfer learning and meta-learning.
What Does Backbone Mean in Neural Networks?
Filed under Deep Learning, Machine Learning
A quick an practical guide to backbones in neural networks.
Getting the Closest String Match
Filed under Algorithms
A quick and practical guide to finding the closest string matches.
What Is Feature Importance in Machine Learning?
Filed under Machine Learning
A guide to feature importance in Machine Learning.
Differences Between Porter and Lancaster Stemming Algorithms
Filed under Algorithms
A comparison between the Porter and Lancaster stemming algorithms.
What Exactly Is an N-Gram?
Filed under Artificial Intelligence, Deep Learning
Learn about n-grams and some practical applications for them.
What Is YOLO Algorithm?
Filed under Computer Vision
A guide to the YOLO algorithm for object detention
Bias Update in Neural Network Backpropagation
Filed under Deep Learning
Learn how to update the bias term with backpropagation.
Convolutional Neural Network vs. Regular Neural Network
Filed under Deep Learning
A comparison between regular neural networks and convolutional neural networks.
What Is Depth in a Convolutional Neural Network?
Filed under Artificial Intelligence, Math and Logic
Understand the term “depth” when it comes to convolutional neural networks.
How to Use K-Fold Cross-Validation in a Neural Network?
Filed under Machine Learning
A guide to validating neural networks with K-Fold Cross-Validation.
Differences Between Bidirectional and Unidirectional LSTM
Filed under Machine Learning
Understand the differences between bidirectional and unidirectional LSTM.
Relation Between Learning Rate and Batch Size
Filed under Deep Learning, Machine Learning
An overview of the learning rate and batch size neural network hyperparameters
Word2vec Word Embedding Operations: Add, Concatenate or Average Word Vectors?
Filed under Deep Learning, Machine Learning
An overview of the word2vec algorithm and the logic behind word embeddings.
Accuracy vs AUC in Machine Learning
Filed under Machine Learning
Learn about two commonly used machine learning metrics, accuracy and AUC.
When Coherence Score Is Good or Bad in Topic Modeling?
Filed under Machine Learning
Learn about Latent Dirichlet Allocation and the coherence score
How to Calculate the Regularization Parameter in Linear Regression
Filed under Machine Learning
Go over an overview of linear regression, and why we need regularization.
Difference Between a SVM and a Perceptron
Filed under Machine Learning
A quick and practical comparison between SVM and a perceptron.
How to Design Deep Convolutional Neural Networks?
Filed under Computer Vision
Learn the basic concepts behind convolutional neural networks, commonly used in computer vision tasks, and how to construct them.
Finding Dates, Times and Addresses in Emails
Filed under Searching
A quick and practical guide to extracting dates, times, and addresses from any text data.
Choosing the best q and p from ACF and PACF plots in ARMA-type modeling
Filed under Math and Logic
Explore some important terms relared to time-series forecasting.
Out-of-bag Error in Random Forests
Filed under Machine Learning
A quick and practical explanation of out-of-bag errors in random forests.
Grey Wolf Optimization Algorithm
Filed under Algorithms, Math and Logic
Learn about the Grey Wolf Optimization (GWO) algorithm and how it works.