Data Analytics Glossary

Meta Description: Learn about variable identification in data analysis. Understand the importance of identifying variables and their types in statistical analysis. Explore examples and resources in our glossary.

Learn about wide tables in data analysis, including their benefits and limitations, and how they are applied in both machine learning and business analytics. Explore key highlights and resources for further reading.

Xgboost is a popular and efficient machine learning algorithm used for classification and regression. It is widely used in data science competitions and can handle both numerical and categorical data. Xgboost can be applied to business applications such as predicting customer churn, fraud detection, and demand forecasting.

iGraph is an open-source software library designed for efficient and easy network analysis. With the ability to program in several languages, including R, Python, Mathematica, and C/C++, iGraph is particularly useful for experts in network analysis. Explore its key features and how it can be applied to businesses for complex network analysis.

Learn about node2vec, a technique for learning vector representations of nodes in a graph. Developed by Aditya Grover and Jure Leskovec in 2016, node2vec is a powerful tool for graph analysis and can be used for various applications, such as recommendation systems, anomaly detection, and link prediction. Discover how to apply node2vec to business and improve customer engagement and fraud detection.

Learn about word2vec, a machine learning algorithm that produces word embeddings, vector representations of words. Word2vec can be used to train other machine learning models for natural language processing tasks, such as sentiment analysis, text classification, and machine translation. Discover how to apply word2vec to business for sentiment analysis, customer segmentation, and content recommendation.