Knowledge graphs are becoming increasingly important in NLP due to their ability to model the relationships between entities and concepts in a structured format. This structured representation of knowledge enables more advanced natural language understanding and generation. How Knowledge Graphs are Used in NLP Knowledge graphs use a graph-based representation where nodes represent entities, and edges represent…

Time series forecasting predicts future values based on past data patterns and has wide applications in various fields such as finance, engineering, and social sciences. Importance of Time Series Forecasting Time series forecasting aids decision-making by predicting future trends and patterns based on past data. It optimizes operations and has applications in various fields such…

Clustering is a technique in unsupervised machine learning where data points are grouped into subsets, or clusters, based on their similarity or proximity to each other. Clustering has many applications in various fields such as data analysis, image processing, natural language processing, and bioinformatics, among others. 1. K-Means Clustering K-Means Clustering is a…