From the course: Choosing the Right ML Approach for Your Business Case with ISO/IEC 25053:2022
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ML model (Clause 6.3)
From the course: Choosing the Right ML Approach for Your Business Case with ISO/IEC 25053:2022
ML model (Clause 6.3)
- Without a blueprint, a building couldn't be built in a predictable way that represents the intended function. The machine learning model is the blueprint for the building of artificial intelligence. In machine learning, a model is the mathematical representation of a system, process, or concept designed to make predictions or inferences about data. It acts as a blueprint for understanding relationships within data and is used to generalize from examples to predict new outcomes. Models learn patterns from data during the training process and apply these patterns to make decisions on unseen data. They are the core of any machine learning or artificial intelligence system. Let's review the primary components that make up the machine learning process. The first is input data. This would contain the features or variables that are fed into the model. This can be structured as in numerical or a categorical or unstructured, as in images, text and audio. The algorithm is the method used by…
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Contents
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Task and general (Clause 6-6.2)2m 14s
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(Locked)
Task details (Clauses 6.2.2-6.2.7)4m 44s
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(Locked)
ML model (Clause 6.3)4m 13s
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(Locked)
ML data (Clause 6.4)3m 33s
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(Locked)
Tools and data preparation (Clauses 6.5-6.5.2)3m 22s
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(Locked)
Support vector machines ML (Clause 6.5.3.5)3m 58s
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(Locked)
Bayesian ML (Clause 6.5.3.3)3m 11s
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(Locked)
Decision tree ML (Clause 6.5.3.6)3m 5s
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