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- Minimum Viable Data Description: Minimum Viable Data (MVD) refers to the smallest amount of data necessary to meet specific business requirements of an(...) Read more
- Multi-Source Data Description: ‘Multi-Source Data’ refers to information collected from various origins, allowing for a more comprehensive and enriched view of a(...) Read more
- Model Optimization Description: Model optimization is the process of improving the performance of a machine learning model by adjusting its parameters. This(...) Read more
- Micro-batch Description: A micro-batch, in the context of data processing, refers to a small batch of data processed in a streaming environment. This(...) Read more
- Machine Learning Library Description: The Machine Learning Library in Apache Flink is a collection of algorithms and tools designed to facilitate the implementation of(...) Read more
- Multi-language Support Description: Multilingual support refers to the ability of a system, software, or platform to handle multiple programming languages, allowing(...) Read more
- Memory-based Learning Description: Memory-Based Learning is an approach within machine learning that focuses on utilizing past experiences to improve decision-making(...) Read more
- Meta-Modeling Description: Meta-modeling is the process of creating models that can be used to create other models, allowing for greater flexibility and(...) Read more
- Multi-Task Learning Description: Multi-task learning is an approach in machine learning where a model is trained to perform multiple tasks simultaneously. This(...) Read more
- Minimum Variance Description: Minimum variance is a fundamental principle in statistics that seeks to minimize the variability of an estimator, resulting in(...) Read more
- Metadata Anonymization Description: Metadata anonymization is the process of removing or altering metadata to prevent the identification of individuals from the data.(...) Read more
- Masking Algorithms Description: Masking algorithms are tools specifically designed to effectively implement data masking techniques. Their primary goal is to(...) Read more
- Machine Learning for Anonymization Description: Machine learning for anonymization refers to the use of advanced artificial intelligence techniques to enhance personal data(...) Read more
- Masking Framework Description: The masking framework is a structured approach to implementing data masking across various systems and processes. This method(...) Read more
- Masking Techniques for Databases Description: Data masking techniques are specific methods applied to the protection of sensitive information by transforming original data into(...) Read more
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