What is feature scaling in machine learning? Feature scaling is a preprocessing technique used in machine learning and data analysis…
What is k-fold cross-validation? K-fold cross-validation is a popular technique used to evaluate the performance of machine learning models. It…
Introduction to word embeddings Word embeddings have become a cornerstone of Natural Language Processing (NLP), transforming how machines process and…
What is fuzzy name matching? A fuzzy name matching algorithm, or approximate name matching, is a technique used to compare…
Graph Neural Network (GNN) is revolutionizing the field of machine learning by enabling effective modelling and analysis of structured data.…
What is few-shot learning? Few-shot learning is a machine learning technique that aims to train models to learn new tasks…
Why Combine Numerical Features And Text Features? Combining numerical and text features in machine learning models has become increasingly important…
L1 and L2 regularization are techniques commonly used in machine learning and statistical modelling to prevent overfitting and improve the…
What is hyperparameter tuning in machine learning? Hyperparameter tuning is critical to machine learning and deep learning model development. Machine…
What is CountVectorizer in NLP? CountVectorizer is a text preprocessing technique commonly used in natural language processing (NLP) tasks for…