Supervised Learning
-
How to Perform ML Alogorithm Evaltuation?
.
Evaluating machine learning models is more than just checking accuracy. It is about understanding how a model behaves under different conditions and ensuring it aligns with business goals. Whether…
-
How to Compare Machine Learning Models – Final Report
.
Introduction Machine learning provides a wide range of algorithms that can be used to solve prediction and classification problems. However, choosing the right model is an important part of…
-
Finding The Best Supervised and Unsupervised Machine Learning Models
.
Machine learning models involves choosing the right approach for a particular problem and evaluating whether the selected model performs reliably. As part of my Data Science internship at Valentius…
-
What is Supervised Machine Learning?
.
Machine learning is one of the most important areas of modern artificial intelligence (AI). It allows computers to learn patterns from data and make predictions or decisions without being…
-
Supervised Learning: Comparing 5 Machine Learning Classification Algorithms
.
Introduction Supervised Learning is one of the most widely used approaches in machine learning for solving classification and prediction problems. In this project, I explored supervised learning by comparing…
-
Machine Learning Model Comparison: Supervised and Unsupervised Learning on the Titanic Dataset
.
Introduction Machine Learning offers several approaches for solving prediction and pattern-discovery problems. Selecting the right algorithm is important because different algorithms can behave differently on the same dataset. In…
-
Supervised Learning: Comparing 5 Machine Learning Algorithms on a Real Dataset
.
A practical comparison of five supervised learning algorithms—Logistic Regression, Decision Tree, KNN, SVM, and Naive Bayes—trained on the same real-world dataset and evaluated using consistent preprocessing and classification metrics.