Inductive Logic Programming
Inductive Logic Programming (ILP) is a subfield of machine learning and artificial intelligence that combines concepts from both logic programming and machine learning. It focuses
Understanding Precision and Recall
Precision and recall are two fundamental metrics used to evaluate the performance of classification models in machine learning and deep learning. In this article, learn
Understanding Overfitting in Machine Learning
Overfitting is a common problem in machine learning and deep learning where a model learns the training data too well, to the extent that it
Introduction to Cross Validation
Cross-validation is a crucial technique in machine learning for evaluating the performance of a predictive model. It involves partitioning the dataset into complementary subsets, performing
Random Forest vs Decision Trees
If you are new to machine learning, you may have come across the terms random forest classifier and decision trees and are now curious about