Louvain Algorithm
Community detection is one of the most important problems in network science: given a graph, how do we find groups of nodes that are more densely connected to each other…
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Data Science and AI
37 posts
Label Propagation Algorithm
What is Label Propagation Algorithm? Label Propagation Algorithm (LPA or LAP) is a simple, fast, and intuitive semi-supervised (and unsupervised) graph-based method for community detection and label inference on graphs.…
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Random Forest Algorithm
What is Random Forest? Random Forest is an ensemble learning method for classification and regression that builds a collection (a “forest”) of decision trees and combines their predictions to produce…
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Latent Semantic Analysis
Latent Semantic Analysis (LSA) is a foundational technique in natural language processing and information retrieval that uncovers hidden (latent) relationships between words and documents. It transforms raw text into a…
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Gradient Boosting Algorithm
Gradient Boosting is one of those rare ideas in machine learning that’s both simple at its core and remarkably powerful in practice. From credit scoring and click-through prediction to anomaly…
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Girvan–Newman Algorithm
What is the Girvan–Newman Algorithm? The Girvan–Newman (GN) algorithm is a classic community detection method for networks (graphs). It identifies clusters (communities) by iteratively removing edges that act as “bridges”…
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Linear Regression
What is the Linear Regression Algorithm? Linear regression is a supervised learning algorithm that models the relationship between one or more input variables (features) and a continuous output variable (target)…
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Top 10 Research Areas in Natural Language Processing (NLP)
Natural Language Processing (NLP) is one of the most dynamic fields in artificial intelligence, driving breakthroughs in communication between humans and machines. This blog explores the Top 10 Research Areas…
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Apriori Algorithm in Data Mining: Working, Applications & Association Rule Learning
What is Apriori Algorithm? Large transactional databases can be mined for frequent itemsets and association rules using the traditional Apriori approach. Finding patterns of items that commonly co-occur in transactions…
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Gated Recurrent Unit (GRU): Architecture, Working & Applications in Deep Learning
What is Gated Recurrent Unit (GRU) Algorithm? A particular kind of Recurrent Neural Network (RNN) architecture called the Gated Recurrent Unit (GRU) is used to simulate sequential data, including speech,…
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