From the course: Choosing the Right ML Approach for Your Business Case with ISO/IEC 25053:2022

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Data acquisition and preparation (Clauses 8-8.3)

Data acquisition and preparation (Clauses 8-8.3)

From the course: Choosing the Right ML Approach for Your Business Case with ISO/IEC 25053:2022

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Data acquisition and preparation (Clauses 8-8.3)

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- Throughout this course, I've used the vehicle analogy with its engine steering and fuel to represent artificial intelligence, machine learning, the algorithm selected and the data. Imagine the additional effort, cost, and time that it took to make a car before Henry Ford established the moving assembly line to mass produced cars. When producing machine learning models and systems, it's imperative that we likewise maintain a systemic or a system approach, lest we incur unnecessary delays, cost and effort. In this video, I will introduce the machine learning pipeline and the initial phase of data acquisition. The initial stage of the machine learning pipeline concerns data acquisition. The data selected aligns with the intent of the business requirement. Just as there are different fuels for different engines, there is different data for different machine learning models. In our example of our AI malicious traffic detector, data collection can be fixed or static, like logs or a stream…

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