Unsupervised Machine Learning Archives

Unsupervised Machine Learning

Unsupervised Machine Learning refers to a type of machine learning where the model is trained on data without labeled outputs. The algorithm tries to identify hidden patterns or structures in the data, such as clustering similar data points or reducing the dimensionality of the data. Common techniques include clustering, anomaly detection, and principal component analysis (PCA). Unsupervised learning is used in applications such as customer segmentation, anomaly detection, and data compression.

Introduction to Machine Learning in Chemical Engineering: Types, Applications, and Examples

AIML in Chemical Engineering / All Info ChE

Machine Learning in Chemical Engineering has become a vital tool in recent years. It aids in everything from process optimization to predictive maintenance. At its core, machine learning allows systems to learn from data. This learning makes it possible to solve complex engineering challenges by identifying patterns and relationships. This article explains three main types […]

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