
Machine Learning-based Matching
Machine Learning-based Matching refers to the process of using machine learning algorithms to match two or more datasets based on their similarities and differences. This process involves training a machine learning model on a set of labeled data to learn the patterns and relationships between the data points. Once the model is trained, it can be used to predict the similarity between new data points and match them accordingly. Machine Learning-based Matching is widely used in various applications such as recommender systems, fraud detection, and image recognition.
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